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Living cells constantly sense and respond to environmental changes. Transcription, the process by which DNA is transcribed into RNA, serves as a critical bridge between external signals and gene expression, ultimately shaping cellular behavior. To unravel the transcription dynamics and the relationship between input signals and gene expression output, various transcription models have been developed. This review explores these common models, their computational frameworks, and the resulting distributions for mRNA number and transcriptional event duration, which offer valuable insights into input-output relationships and underlying response mechanisms. We further analyze how different promoter types, chromatin environments, and network motifs influence these relationships. Finally, we probe how information theory can be applied to systems with near-maximum channel capacity to reveal the dynamic range of t ranscription factor concent rat ions, input-output dynamics, and the link between these factors and gene expression distribution. Through these multifaceted analyses, we identify key regulators of dynamic input-output relationships and gain deeper insights into how genes respond to transcription factor signals. Quantitative studies of input-output relationships hold promises for identifying key regulatoiy factors, predicting changes in gene expression patterns, and designing interventions to manipulate cellular functions and behavior. [ABSTRACT FROM AUTHOR]

Addressing the issue of information asymmetry in crowdfunding, this paper developed a new model for predicting crowdfunding performance, based on the decision utility rules for processing uncertain information in prospect theory and combining the analysis of crowdfunding project information disclosure with investor utility. To tackle the issue of excessive feature selection in practical applications, it introduced a sparsity-based feature selection method using neural networks, which could help crowdfunding platforms to focus on core features for better understanding and predicting investor behavior. Empirical analysis of over 150 000 projects on the Kickstarter platform shows that models considering investors perception of risk and prospect utility have better predictive and explanatory power for crowdfunding performance. The research results not only provide a new perspective for the prediction and evaluation of crowdfunding projects, but also offer powerful tools for crowdfunding platforms and fundraisers to establish models for analyzing backers backing behavior. [ABSTRACT FROM AUTHOR]

To address the problems of scientific theory, common technology and engineering application of multimedia and multimodal information computing, this paper is focused on the theoretical model, algorithm framework, and system architecture of brain and mind inspired intelligence (BMI) based on the structure mechanism simulation of the nervous system, the function architecture emulation of the cognitive system and the complex behavior imitation of the natural system. Based on information theory, system theory, cybernetics and bionics, we define related concept and hypothesis of brain and mind inspired computing (BMC) and design a model and framework for frontier BMI theory. Research shows that BMC can effectively improve the performance of semantic processing of multimedia and cross-modal information, such as target detection, classification and recognition. Based on the brain mechanism and mind architecture, a semantic-oriented multimedia neural, cognitive computing model is designed for multimedia semantic computing. Then a hierarchical cross-modal cognitive neural computing framework is proposed for cross-modal information processing. Furthermore, a cross-modal neural, cognitive computing architecture is presented for remote sensing intelligent information extraction platform and unmanned autonomous system. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Data Acquisition & Processing / Shu Ju Cai Ji Yu Chu Li is the property of Editorial Department of Journal of Nanjing University of Aeronautics & Astronautics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

It is a basic and challenging task to identify important nodes in hypernetworks, and the related research is of great value for further analysis of network topology and functional characteristics. In order to break through the limitations of the existing important node recognition methods, an important node recognition method based on node propagation entropy is proposed by using hypergraph and information entropy theory. This method takes into account both local and global topology information of nodes, uses the node clustering coefficient and the number of neighbors to represent the local propagation influence of node information, the global influence of the node information is reflected by the shortest path between nodes and K-shell centrality, and fully considers the influence of nodes and their neighbors, the importance of nodes in the network is represented by the size of node propagation entropy finally. Using monotonicity, robustness and SIR propagation model evaluation criteria, compared with other methods on six real networks from different fields, experimental results show that the proposed method can identify the important nodes in the hypernetwork accurately and effectively. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Distance Education (1672-0008) is the property of Zhejiang Open University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Engineering Management / Gongcheng Guanli Xuebao is the property of Journal of Engineering Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Hebei University of Science & Technology is the property of Hebei University of Science & Technology, Journal of Hebei University of Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Shanghai Jiao Tong University (1006-2467) is the property of Journal of Shanghai Jiao Tong University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Engineering Management / Gongcheng Guanli Xuebao is the property of Journal of Engineering Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Ordnance Industry Automation is the property of Editorial Board for Ordnance Industry Automation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The aim of this research is to study how to reasonably share the risks of the EPC project consortium and promote the smooth implementation of the EPC project. Firstly, on the basis of literature analysis and expert interviews, the index system of risk factors of the EPC project consortium is established. The risk factors are initially shared by the static game theory of complete information. Secondly, a revised index system of risk sharing is constructed for shared risks, using G1 model. Finally, an improved Shapely model is constructed by taking natural risks as an example to determine the reasonable risk sharing ratio of the EPC project consortium, and further verify the validity of the model. [ABSTRACT FROM AUTHOR]

The complicated technical interface and numerous interface participants of the railway engineering in difficult and dangerous mountainous areas increase the difficulty of technical interface management, and information exchange is an important guarantee for effective interface management. In order to achieve efficient technical interface information exchange, a comprehensive evaluation model of the technical interface information exchange level of railway bridge and tunnel engineering in difficult and dangerous mountainous areas is proposed based on IFAHP-two-dimensional cloud. According to the theory of information communication, the influencing factors of technical interface information exchange between railway bridges and tunnels in difficult and dangerous mountainous areas are analyzed to construct a comprehensive evaluation index system for technical interface information exchange, and IFAHP is used as the indicator to assign weights. The information exchange level of the technical interface is evaluated through the two-dimensional cloud model, the comprehensive evaluation cloud diagram is drawn with MATLAB to directly reflect the evaluation results, and the closeness of the comprehensive evaluation cloud to the standard cloud is calculated to determine the final evaluation level. The technical interface between the Dagala Tunnel and the Dongga-Yarlung-Zangbo River Bridge is referenced to evaluate the level of information exchange, and the applicability and effectiveness of the model are verified. [ABSTRACT FROM AUTHOR]

To evaluate the multi-dimensional dynamic safety risks in the deep foundation pit excavation process of urban subway station, a safety risk evaluation method was proposed based on information entropy theory. The entropy method was used to calculate the objective weight value of each safety risk index. In addition, each single safety risk evaluation value and the comprehensive safety risk evaluation value were further proposed to evaluate the safety risk state of single risk evaluation index and the overall safety risk state during the process of deep foundation pit excavation. Combined with the above mentioned two kinds of indexes and the safety risk level evaluation system, the quantitative description of safety risk status is obtained. The safety risk of the deep foundation pit excavation construction process of Anhui Hefei metro station line 7 was further evaluated. The results show that this proposed method can effectively evaluate the safety risk state in the deep foundation pit excavation process. Furthermore, it also can effectively identify the key risk indicators at different construction stages, which provide some technical supports for the safety risk management in the deep foundation pit excavation construction process. [ABSTRACT FROM AUTHOR]

Copyright of South Architecture / Nanfang Jianzhu is the property of South Architecture Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Signal Processing is the property of Journal of Signal Processing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Mutual information-based filtering feature selection algorithms are often limited to the metric of mutual information. In order to circumvent the limitations of adopting only mutual information, a distance metric-based algorithm RReliefF is introduced on the basis of mutual information to obtain better filtering criteria. RReliefF is used for the classification tasks to measure the relevance between features and labels. In addition, maximal information coefficient(MIC) is used to measure the redundancy between features and the relevance between features and labels. Finally, entropy weight method is applied to objectively weigh the MIC and RReliefF. On this basis, a filtering feature selection algorithm based on entropy weight method(FFSBEWM) is proposed. Comparing experiments carried out on 13 data sets show that the average classification accuracy and highest classification accuracy of the feature subsets selected by the proposed algorithm are higher than those of the comparison algorithms. [ABSTRACT FROM AUTHOR]

Copyright of Lubrication Engineering (0254-0150) is the property of Editorial Office of LUBRICATION ENGINEERING and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Jilin University (Science Edition) / Jilin Daxue Xuebao (Lixue Ban) is the property of Zhongguo Xue shu qi Kan (Guang Pan Ban) Dian zi Za zhi She and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

For the hydrometeor classification problem of dual-polarization weather radar with low data resolution, a hydrometeor classification method based on modified wavelet transform interpolation tree augmented naive Bayesian (TAN) is proposed. Firstly, it is necessary to carry out modified wavelet transform interpolation when the resolution of the original radar polarization parameter data is relatively low, so as to obtain high resolution radar polarization parameter data. Then, based on the mutual information theory, the discrete high resolution polarization parameter data are used to train the TAN network structure and parameters, and the TAN network which can be used for hydrometeor classification is obtained. Finally, the high resolution radar polarization parameter data are brought into the final TAN network to realize the hydrometeor classification. The processing results of measured data show that the proposed method can achieve better classification results of hydrometeor for low resolution radar polarization parameter data. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Frontiers of Computer Science & Technology is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Target detection is the basic function of radar, and its robustness directly determines the success or failure of radar application. Aiming at the problem of Rayleigh target detection, a robust radar target detection method is proposed by making full use of the advantages of continuous belief function theory in uncertain information representation and reasoning. The belief of prior model noise, real target and external interference can be quantified accurately in the detection decision space. In view of the fact that the proposed method does not have analytical solution, through the transformation of random variables, the arbitrary Rayleigh target amplitude fluctuation model is transformed into the standard Rayleigh model. And then, the numerical calculation of the belief function is realized by using the look-up table method. Finally, the detection decision is completed or used for subsequent fusion reasoning. Rayleigh target detection experiments verify the robustness of the proposed method. [ABSTRACT FROM AUTHOR]

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

One of the major problems of multi-sensor information fusion is that sensors frequently produce spurious observations, which have a great impact on the fusion accuracy and are difficult to be modeled and predicted. Bayesian information fusion technology based on entropy theory is an effective method to solve this problem. However, this method needs the integral operation in infinite interval, and the problem of numerical instability is prone to occur. To solve this problem, this paper proposes an improved multisensor data adaptive fusion method. In the framework of Bayesian theory, we use the difference between the measured values of sensors to adaptively establish the posterior probability distribution model of the sensor. Combined with the theory of mutual information, the pseudo measured values can be identified and eliminated in real time, without integral calculation. The simulation and measured data test results show that the proposed method achieves the same results as the simple Bayesian fusion method without any spurious measurement, and the information fusion performance is obviously better than the simple Bayesian fusion method. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Data Acquisition & Processing / Shu Ju Cai Ji Yu Chu Li is the property of Editorial Department of Journal of Nanjing University of Aeronautics & Astronautics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Image & Graphics is the property of Editorial Office of Journal of Image & Graphics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper presents a new method for describing the complexity of geographic line elements. Firstly, the Fourier series is used to transform the geographic line elements from the spatial domain to the frequency domain for analysis. Fourier expansions are performed on different geographic line elements to obtain different Fourier descriptors, then we use the method of setting the area threshold to control the deviation of the geographic elements before and after the Fourier expansion to a certain extent, so that the curve reduced by the Fourier descriptor can replace the original geographic line elements. Secondly, based on Shannon’ s information entropy theory, the amount of information of the fitted curve after Fourier expansion is calculated. Then, by combining the frequency domain with the fractal theory, the data of the amount of information is further processed based on the Head‐tail data break and Koch’ s Two‐Eighth Law, and the concept of the distribution index p is proposed. Finally, the distribution index and the square root model are combined, and the approximate expression of the distribution index of the map at different scales is obtained by the least squares method. We select the contour data of a region to conduct experiments, and experiment results show that the distribution index has a good expression effect on the complexity of geographic line elements at different scales, and can be applied to multi‐scale expression of line elements. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Image & Graphics is the property of Editorial Office of Journal of Image & Graphics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Image & Graphics is the property of Editorial Office of Journal of Image & Graphics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Mechanical Engineering is the property of Editorial Board of China Mechanical Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In view of the NIMBY group events evoked by the public opinion in recent years, this paper studies the evolution of NIMBY opinion from the perspective of public perception for the NIMBY project and governmental guidance to the public opinion. Firstly, through multiple cases comparative analysis, the evolution characteristics of NIMBY opinion are extracted macroscopically, and is described based on the Gompertz model improvement. Subsequently, the cognitive interaction behavior of individuals to the NIMBY project is analyzed from the micro perspective, and the dynamics of individual replication is described based on the evolutionary game modeling. At the same time, considering the government's response to NIMBY opinion through the positive opinion, the cross-entropy model and dynamic equation of the government by the guidance to NIMBY opinion are constructed based on the information entropy theory and the dynamic method. Then, on this basis, the evolution model of NIMBY opinion with the "public-government" is proposed. Finally, the existence and stability of the equilibrium point of the model are discussed and applied to a numerical simulation study, taking evolution of NIMBY opinion for the Maoming PX event in Guangdong as example. The results show that:When the public perception difference for the risk of NIMBY project is small, the government should properly respect the NIMBY opinion, and follow the gradual guidance path to give a timely, actively and concerned response to the NIMBY opinion. Otherwise, the NIMBY opinion will become more and more popular. When the public perception is very different, the government should strengthen the tracking and supervision for the NIMBY opinion, and give a timely, appropriate and objective response to NIMBY opinion. Otherwise, the NIMBY opinion will evolve to a higher steady state. [ABSTRACT FROM AUTHOR]

Existing image fusion algorithms have some problems caused by non-linear operations, such as noise interference and spatial complexity, which make fused images easy to cause distortion and information loss. Compressed sensing image fusion algorithms proposed by some scholars can effectively improve this problem. However, most of them neglect the low rank of image matrix, thus often reducing the quality of fusion. Thus, combining the compressed sensing fusion technology with the low rank matrix approximation method, we propose an image fusion method based on information theory image difference and adaptive weighted kernel norm minimization. The method consists of three stages. Firstly, the two source images are sparsed by wavelet sparse basis, and the measurement output matrix is obtained by compressing the samplings with structural random matrix. Then, the measurement output matrix is divided into blocks, and the fused measurement output matrix blocks are obtained by using the image difference fusion algorithm. Finally, the block weights obtained by adaptive weighted kernel norm minimization method are used to reconstruct the fused image by the orthogonal matching pursuit method. Experimental results verify the validity and universality and show that our method is superior to other fusion algorithms in many evaluation indexes. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) is the property of Chongqing University of Posts & Telecommunications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With diversification of data acquisitions and associated technologies, there is steady accumulation of multi-source spatial data, prompting more research on effective and fast data integration to provide information and technical support for geospatial research and applications. In this paper, procedures for integrating multi-source data are referred to as data fusion. Research developments are reviewed by considering them as classic and extended types of methods, respectively. To review the progress in classic methods for data fusion and related data processing, this paper clarifies some of the relatively well-established methods using a typology of object-and field-based models of spatial data. For extended methods, the paper discusses multi-point geostatistics, statistical-mechanistic methods, multi-scale signal analysis and reconstruction, and information-theoretic strategies. Some of the issues, such as scale mismatch, semantic inconsistency, and the temporal dimension, are discussed in the hope of better supporting the fusion of multi-sourced and heterogeneous data. Further research will enhance theoretical foundations of geographic information to enrich methodologies for spatial data and their analyses, and help add to the applicability and value of spatial information. [ABSTRACT FROM AUTHOR]

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Community structure can provide a medium-scale analysis perspective for other analysis in the networks, and its research is fundamental and important in complex networks. In complex networks , the overlapping community structure is a more actual description of the structure of social networks. So analyzing the structure of overlapping communities has practical significance. After studying the existing overlapping community detection algorithms combined with certain knowledge of information theory, we define the concept of community from the perspective of information theory, and present an algorithm which can detect the overlapping community structure in complex networks on the basis of information dissemination theory. Experiments show that compared with the traditional definition of community and detection algorithms, the proposed algorithm has a more accurate physical meaning and a lower time complexity. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Signal Processing is the property of Journal of Signal Processing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Information geometry is a set of system info originated from the study on the geometry properties of statistical manifold, which offers one kind of new thinking and method to the radar signal processing problems. A new kind of view to radar target detection problem is given based on information geometry theory in this article,simultaneously,information geometry method to radar target detection is also proposed by defining the distance between the null and alternative distribution on statistical manifold. The information geometry method to radar target detection is achieved by comparing the distance between oberserved distribution and the hypothetical distribution when target exists or not. Moreover, it is easy to be accomplished by translating radar target detection problem into geometry problem on statistical manifold. Finally, detection performance of information geometry method and likelihood ratio detector is compared by simulations. [ABSTRACT FROM AUTHOR]

Point cloud registration is the important part in the large-scale city reconstruction. Considering the ground plane and buildings, which are the main objects in the city, always consist of several planes, we propose a new method that registering large-scale point clouds together through matched planes. For extracting the planes exactly from the point cloud, this paper presents a novel co-clustering method that clusters data points and hypotheses simultaneously. The traditional methods only cluster the data points, so they will fail to extract some planes. After knowing the planes, we use the random sample method to match the planes. The transformation matrix between the point clouds is calculated from the matched planes. Experimental results not only show that the co-clustering method can extract the planar structure more accurate and robust, but also demonstrate the effectiveness of the novel registration method for the city point clouds. Since the process in our method is only performed to the sparse version of the point clouds, it reduces the amount and complexity of calculation, which makes it to be suitable for the large-scale city reconstruction. [ABSTRACT FROM AUTHOR]

This paper studies joint beamforming and power allocation for maximizing the minimum signal-to-interferenceplus-noise ratio optimization problem in multi-cell multiuser multiple-input single-output downlink network. To solve the original downlink non-convex optimization problem, the original optimization problem is transformed into an equivalent uplink optimization problem. Although the beamformer and power allocation can be obtained by the iterative algorithm in the finite system, it depends on the instantaneous channel state information which requires instantaneous power update. To reduce the complexity of power updating, an algorithm that only requires statistical channel state information is designed to derive power allocation by applying the random matrix theory. Numerical results validate the effectiveness of our proposed algorithm and show the advantages of our proposed algorithm over maximal-ratio transmit in the single base station power constraint. [ABSTRACT FROM AUTHOR]

In modern keyword spotting implementation, lattice combining is a useful method. Regrettably, it can result in massive redundant information which leads to a slow indexing. This paper propose a keyword spotting method based on lattice intersecting. Firstly, we take the intersection of two lattices, and combining the acoustic score and language score on the same path. Secondly, in order to solve the problem of gaps in the intersection lattice, we use the best single lattice to supplement it. Finally, the intersection lattice will be used for retrieval. With intersection lattice, it utilized the scores of each sub lattice. Without degrading the lattice coverage accuracy, it substantially eliminated redundant information and decreased indexing volume. The experimental results show that keyword spotting can improve 5. 3% quality compared to lattice combining referred to keyword spotting ATWV indicator. [ABSTRACT FROM AUTHOR]

Saliency detection is an important task in computer vision and image processing. The most influential factor in bottom-up visual saliency is contrast operation. In this paper, we propose a unified model to combine widely used contrast measurements, namely, center-surround, corner-surround and global contrast to detect visual saliency. The proposed model benefits from the advantages of each individual contrast operation, and thus produces more robust and accurate saliency maps. Extensive experimental results on natural images show the effectiveness of the proposed model for visual saliency detection task, and demonstrate the combination is superior to individual subcomponent. [ABSTRACT FROM AUTHOR]

For improving the correctness of SELCALL decoder, a decoding algorithm based on the energy centrobaric method is proposed. The estimated values of signal frequency and amplitude are regulated by the energy centrobaric method, and the state machine is designed for the decoding flow. The simulation in strong-noisy environment and the lab test on a certain type airplane are done to verity the effectiveness of the proposed algorithm. The results show that the decoder is useful for a long time test when the proposed algorithm is used. The estimated frequency value is almost unbiased and the estimated amplitude error is less than 10% . So the decoding algorithm based on the energy centrobaric method is applicable in airborne SELCALL system [ABSTRACT FROM AUTHOR]

Same sampling rate of each sub-block in each sub-band is gained when the multi-scale block compressed sensing algorithm (MS-BCS-SPL) subdivides sub-band information of each layer into blocks. But unreasonable resource distribution would be caused if image sub-blocks have different edge information. In this thesis, on basis of MS-BCS-SPL, multi-scale block compressed sensing adaptive sampling is realized by distributing total sampling rate into all sub-block of each sub-band, which uses the difference of edge information and directivity of image blocks. First the edge information of image blocks is calculated and the direction is estimated, through which the total sampling rate is assigned adaptively into each block of each sub-band by the characteristics of the wavelet transform, realizing adaptive multi-scale block compressed sensing. It is shown by experiments that compared with algorithm of MS-BCS-SPL, by using adaptive multi-scale block compressed sensing algorithm, with different sampling rate especially lower sampling rate, not only less samples is used and resources are saved, also high quality images are reconstructed and reasonable resources distribution is achieved. [ABSTRACT FROM AUTHOR]

Hyperspectral image has some typical characteristics such as too many of bands, hard to obtain labeling samples, easy of being interfered of spectral information. These characteristics lead to the dimensionality disaster and the spatial variability of spectral information. To solve these problems, it is proposed to introduce dissimilarity in Laplacian support vector machine (Diss-LapSVM) by the adding dissimilarity information to machine' manifold regularization term, which restrains the influence of the spatial variability effectively. Meanwhile, in order to introduce appropriately distribution of unlabeled samples, This paper provides linear neighborhood propagation (LNP) to construct graph Laplacian matrix. The results illustrated that the proposed method can improve the classification accuracy, especially for samples which have similar spectral features. [ABSTRACT FROM AUTHOR]

In many application scenarios, a low complexity video encoder is needed, the combine of distributed video coding and compressive sensing technique is fit for these scenes. So a new video coding scheme, distributed video compression coding, appears. In some distributed video compression coding schemes, the video frames are encoding independently at the coder and decoding jointly at the decoder. Specifically, the key frames decode independently and non-key frames decode with the help of the side information which is generated by key frames. This ignores the correlations between non-key frames. This paper proposes a new distributed video coding scheme, dividing the non-key frames into the main non-key frames and sub-non-key frames. The main non-key frames decode with the help of the side information which is generated by key frames. The sub-non-key frames make use of the adjacent main non-key frames to predict the measurement firstly. Then the sub-non-key frames decode with the side information which is generated by key frames. The experimental results show that the proposed scheme improves the PSNR of non-key frames there 2dB ~4dB. [ABSTRACT FROM AUTHOR]