Search

To model a true three-dimensional (3D) display system, we introduced the method of voxel molding to obtain the stereoscopic imaging space of the system. For the distribution of each voxel, we proposed a four-dimensional (4D) Givone-Roessor (GR) model for state-space representation--that is, we established a local state-space model with the 3D position and one-dimensional time coordinates to describe the system. First, we extended the original elementary operation approach to a 4D condition and proposed the implementation steps of the realization matrix of the 4D GR model. Then, we described the working process of a true 3D display system, analyzed its real-time performance, introduced the fixed-point quantization model to simplify the system matrix, and derived the conditions for the global asymptotic stability of the system after quantization. Finally, we provided an example to prove the true 3D display system's feasibility by simulation. The GR-model-representation method and its implementation steps proposed in this paper simplified the system's mathematical expression and facilitated the microcontroller software implementation. Real-time and stability analyses can be used widely to analyze and design true 3D display systems. [ABSTRACT FROM AUTHOR]

This paper presents an effective machine learning-based depth selection algorithm for CTU (Coding Tree Unit) in HEVC (High Efficiency Video Coding). Existing machine learning methods are limited in their ability in handling the initial depth decision of CU (Coding Unit) and selecting the proper set of input features for the depth selection model. In this paper, we first propose a new classification approach for the initial division depth prediction. In particular, we study the correlation of the texture complexity, QPs (quantization parameters) and the depth decision of the CUs to forecast the original partition depth of the current CUs. Secondly, we further aim to determine the input features of the classifier by analysing the correlation between depth decision of the CUs, picture distortion and the bit-rate. Using the found relationships, we also study a decision method for the end partition depth of the current CUs using bit-rate and picture distortion as input. Finally, we formulate the depth division of the CUs as a binary classification problem and use the nearest neighbor classifier to conduct classification. Our proposed method can significantly improve the efficiency of interframe coding by circumventing the traversing cost of the division depth. It shows that the mentioned method can reduce the time spent by 34.56% compared to HM-16.9 while keeping the partition depth of the CUs correct. [ABSTRACT FROM AUTHOR]

In this paper, a novel adaptive fuzzy controller is developed for the uncertain fractional-order switched nonlinear systems whose output is quantized by a class of sector-bounded quantizers. Since the states are not completely measurable, an observer with quantized output signal is designed to estimate the unknown system states. Meanwhile, based on the fractional Lyapunov stability criterion, the Lyapunov function with sum functions and the virtual control function with hyperbolic tangent functions are designed. Besides, in order to improve the approximation accuracy of the unknown nonlinear functions generated by fractional differential, the prediction errors and auxiliary variables of series-parallel estimation model are introduced in backstepping procedures. The simulation results show that the control scheme ensures that all the signals of the considered system remain semi-globally uniformly ultimately bounded, and the tracking error converges to a small neighborhood of the origin regardless of arbitrary switching. [ABSTRACT FROM AUTHOR]

This paper investigates the dissipative interval type-2 (IT2) fuzzy control issue for a group of uncertain nonlinear systems subject to randomly occurring sensor saturation and quantization. By utilizing the both lower and upper membership functions with relevant tradeoff moduli, uncertainties, which exist in the considered systems, can be captured effectively. During the design of the IT2 fuzzy controller, we take the actuator failure into consideration. Considering the randomicities for the occurrences of sensor saturation and quantization, two separate Bernoulli stochastic distributed courses are utilized to construct the corresponding complicated transmission route. In term of Lyapunov stability theory, sufficient criteria to design dissipative IT2 fuzzy controller are presented to assure the stochastic stability with strict dissipativity of resulting closed-loop systems. Finally, illustrative example verifies the effectiveness and merits of the control strategy proposed in this paper. [ABSTRACT FROM AUTHOR]

Abstract The optimal modified performance of the multi-input multi-output (MIMO) networked control systems (NCSs) with encoding–decoding, channel noise in the forward channel and packet dropouts, quantization in the feedback channel is investigated in this paper. A new and efficient tracking performance index for the NCSs is presented which prevents variations in the tracking error where there is no integrator in the plant. The optimal modified performance is obtained by the method of coprime factorization and partial fraction. The results demonstrate that the optimal modified performance is related to the locations of the non-minimum phase (NMP) zeros, unstable poles of the given plant as well as their directions. In addition, the modified factor, packet dropouts probability, channel noise and encoding–decoding are also closely related to optimal modified performance of the NCSs. Finally, we present some particular examples to illustrate the theoretical results. Highlights • A new and efficient tracking performance index for the NCSs is presented. • The communication channal is characterized by coding-decoding, channel noise, data dropout and quantization. • The optimal modified performance of MIMO NCS is attained by applying co-prime factorization technique. • The optimal modified tracking performance is constrained by plant internal structure and the multi-communication parameter. [ABSTRACT FROM AUTHOR]

Abstract This paper investigates the problem of observer-based robust H ∞ output feedback control for networked control systems (NCSs) with randomly occurring uncertainties, dynamic quantization, and packet loss. It is assumed that the system measurement output will be quantized by a dynamic quantizer and the random packet loss is represented by Bernoulli random binary distribution. In the presence of randomly occurring uncertainties, dynamic quantization, and packet loss, the attention of this research is focused on the design of observer-based robust H ∞ output feedback controller such that the resulting system is stochastically stable with the prescribed H ∞ noise attenuation level. The sufficient condition for the existence of such output feedback controller is expressed in the form of linear matrix inequality (LMI). Simulation results of two illustrative examples are proposed to demonstrate the effectiveness of the developed design method. Highlights • Robust H ∞ output feedback control problem has been considered for NCSs. • The proposed quantized control strategy is applicable for random signal. • The corresponding design condition is proposed in the form of LMI. [ABSTRACT FROM AUTHOR]

Abstract This paper considers model predictive control (MPC) for the linear discrete-time systems in the presence of packet loss, quantization and actuator saturation. Compared with the previous work ([45]), this paper presents an improved networked MPC approach for networked control systems (NCSs) by applying the quantization dependent Lyapunov function (QDLF) method which leads to less conservative results. The additional improvement is made by placing the heavier weighting on the system corresponding to the actual linear feedback law and choosing the relative weighting on the actual and auxiliary feedback laws which further improves the control performance over the existing method. It is shown that the closed-loop stability is guaranteed and a quantized state-feedback controller is derived by solving the infinite horizon optimization problem. Moreover, this method is further extended to multiple-input case. A numerical example is given to illustrate the effectiveness of the proposed approach. Highlights • We apply the QDLF to analyze the stability of the closed-loop system, which reduces the conservativeness of the existing results. • We introduce a regulated parameter for optimization problem which improves the control performance. [ABSTRACT FROM AUTHOR]

Abstract This paper reports a novel electrocardiogram (ECG) data compression algorithm which employs DCT based discrete orthogonal Stockwell transform. Dead-zone quantization is utilized to apply quantization as well as a threshold condition to transform coefficients. Further, integer conversion of coefficients is performed. It improves compression at the cost of very less reconstruction error. All integer coefficients are encoded using run-length coding. It exploits the repetition of data instances. Run-length coding helps to achieve higher compression without any relevant information loss. Performance of the proposed compression algorithm is evaluated using 48 single channel ECG records which are taken from the MIT-BIH arrhythmia database. A competitive compression performance is observed in comparison with other ECG compression methods. [ABSTRACT FROM AUTHOR]

This article investigates switched quantizers for speech signal depicted with Gaussian probability density function (PDF). Gaussian PDF is better for smaller frame lengths that are represented here. Companding technique results in constant Signal to Quantization Noise Ratio (SQNR). In this paper two approaches are present: quasi-logarithmic (QL) and piecewise uniform (PU) compandor. Simpler compandor directly affects the complexity of hardware realization and expense of given solution, but, on the other hand, also brings to weaker performances. Therefore, a smart choice has to be made. Usage of switched technique leads to better performances. This way, the quality of quantization is improved by dividing the dynamic range of variances into multiple subranges. For each subrange a separate quantizer is designed, with its support region's amplitude. The optimal amplitude is numerically determined, whereby a single criterion is obtaining the maximal SQNR. Bit rates of these quantizers don't depend on signal variance, as the fixed length codes are used. The performances of proposed quantizers are demonstrated on real speech signals from the reliable database. Comparison of obtained results with other recent solutions is done in order to show the efficiency of this model. [ABSTRACT FROM AUTHOR]

High Efficiency Video Coding (HEVC) possesses a special intact coding flow frame that involves four basic procedures: prediction, transformation, quantization and entropy coding. The whole process has high computational complexity, especially the transformation and quantization, which obstruct HEVC for real-time application. To reduce the computational complexity, computing time, or resources, a fast rate-distortion optimized algorithm for HEVC is presented. The rate distortion optimized transformation (RDOT) with reclassification and the rate-distortion optimized quantization (RDOQ) extensional bypass decision method are employed to save the computational complexity. The RDOT performs initial classification and reclassification for each class to simplify the decorrelation of residual data transformation. Moreover, the RDOQ bypass could reduce the computational complexity by skipping the unnecessary candidates of transformation blocks with high computation. Experimental results reveal that the proposed algorithm implemented reduces HEVC coding complexity and achieves almost the same coding performance. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the adaptive control problem for a class of nonlinear uncertain MIMO systems with actuator faults and quantization effects. Under some mild conditions, an adaptive robust fault-tolerant control is developed to compensate the affects of uncertainties, actuator failures and errors caused by quantization, and a range of the parameters for these quantizers is established. Furthermore, a Lyapunov-like approach is adopted to demonstrate that the ultimately uniformly bounded output tracking error is guaranteed by the controller, and the signals of the closed-loop system are ensured to be bounded, even in the presence of at most m − q actuators stuck or outage. Finally, numerical simulations are provided to verify and illustrate the effectiveness of the proposed adaptive schemes. [ABSTRACT FROM AUTHOR]

The paper gives a performance research of re-ranking in sub-image retrieval using scalable vocabulary tree (SVT) which is built from local Speed Up Robust Features (SURF) descriptors. Firstly, the paper gives a study on retrieval performance using different single layers of the tree, which tells it divides data too coarsely for low layers with a small quantity of leaf nodes, while too finely for the 6-th layer with too many leaf nodes. Then using the best selected layer, the authors give a comparative analysis with popular advanced re-ranking strategies in the existing literatures. Finally, the authors propose a weighted score method that calculates matching score from dominating layers. The experimental results prove that the weighted score method achieves almost optimal retrieval performance when using SVT for data representations. Meanwhile, it almost doesn't increase any computational complexity, and can be implemented easily. [ABSTRACT FROM AUTHOR]

Currently, the quantize-and-forward (QF) scheme with high order modulation and quantization has rather high complexity and it is thus impractical, especially in multiple relay cooperative communications. To overcome these deficiencies, an improved low complex QF scheme is proposed by the combination of the low order binary phase shift keying (BPSK) modulation and the 1-bit and 2-bit quantization, respectively. In this scheme, the relay selection is optimized by the best relay position for best bit-error-rate (BER) performance, where the relays are located closely to the destination node. In addition, an optimal power allocation is also suggested on a total power constraint. Finally, the BER and the achievable rate of the low order 1-bit, 2-bit and 3-bit QF schemes are simulated and analyzed. Simulation results indicate that the 3-bit QF scheme has about 1.8~5 dB, 4.5~7.5 dB and 1~2.5 dB performance gains than those of the decode-and-forward (DF), the 1-bit and 2-bit QF schemes, at BER of 10-2, respectively. For the 2-bit QF, the scheme of the normalized Source-Relay (S-R) distance with 0.9 has about 5dB, 7.5dB, 9dB and 15dB gains than those of the distance with 0.7, 0.5, 0.3 and 0.1, respectively, at BER of 10-3. In addition, the proposed optimal power allocation saves about 2.5dB much more relay power on an average than that of the fixed power allocation. Therefore, the proposed QF scheme can obtain excellent features, such as good BER performance, low complexity and high power efficiency, which make it much pragmatic in the future cooperative communications. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of dynamic output feedback control for affine T–S fuzzy systems with quantized measurements. By using the S-procedure, the unmatched regions between the plant and the controller caused by quantization errors are considered in control synthesis. A novel piecewise dynamic output feedback control design is presented, which reduces the worst case peak output due to quantization errors and guarantees an H ∞ -norm bound constraint. In contrast to the existing results, the derived design condition leads to better steady-state performance and less computational burden. Numerical examples are given to show the superiority and effectiveness of the new method. [ABSTRACT FROM AUTHOR]

Matrix synthesis of semiconductor CdS nanoclusters is an actual task because represents a method of obtaining monodisperse and stable nanoparticles. A biopolymer films is the matrix for synthesis of cadmium sulfide nanoparticles by method of a leafwise chemosorption. The structure and optical properties of received samples are investigated. The effect of dimensional quantization for particles of ultradispersions was detected, the band gap and sizes of particles were defined. The nonuniform distribution of monodisperse cadmium sulfide nanoparticles in a matrix was determined. Mainly, they localized on sites of a biopolmer containing calcium. [ABSTRACT FROM AUTHOR]

This paper addresses the H ∞ filtering of continuous Markov jump linear systems with general transition probabilities and output quantization. S-procedure is employed to handle the adverse influence of the quantization and a new approach is developed to conquer the nonlinearity induced by uncertain and unknown transition probabilities. Then, sufficient conditions are presented to ensure the filtering error system to be stochastically stable with the prescribed performance requirement. Without specified structure imposed on introduced slack variables, a flexible filter design method is established in terms of linear matrix inequalities. The effectiveness of the proposed method is validated by a numerical example. [ABSTRACT FROM AUTHOR]

This study aimed to investigate efficient bit-allocation and rate-control methods for H.264 scalable video encoders. We first presented a new bit-allocation algorithm at the frame level for H.264 temporal scalability. Additional to the target bit-rate and buffer occupancy, the temporal hierarchical level and visual complexity were considered for determining the bit budget of a frame. This bit-allocation scheme was followed by a quantization parameter (QP) estimation procedure to achieve the desired bit-rate. We improved the conventional QP assignment by identifying and correcting inappropriate QP values due to incorrect visual complexity prediction. Furthermore, the proposed bit-allocation and rate-control algorithm for temporal scalability was seamlessly integrated with spatial/quality scalabilities to offer flexible bit-rate/quality combinations. Rate-control performance of an investigated method was extensively evaluated in the accuracy of produced bit rates, rate-distortion behavior, and stability of the decoder's buffer occupancy. Experimental results showed that the proposed algorithm achieved accurate bit-rates, prevented buffer overflow and underflow, and simultaneously produced more favorable and stable visual quality as compared to the state-of-the-art approaches in the literature. [ABSTRACT FROM AUTHOR]

This paper proposes a new model of switching scalar quantization that besides the usual adaptation to the variance uses a switching technique for adaptation to the distribution of the speech signal source. By applying the new model a smaller quantization errors achieved in comparison to the conventional models with a usual adaptation. [ABSTRACT FROM AUTHOR]

We propose a new image representation for texture categorization and facial analysis, relying on the use of higher-order local differential statistics as features. It has been recently shown that small local pixel pattern distributions can be highly discriminative while being extremely efficient to compute, which is in contrast to the models based on the global structure of images. Motivated by such works, we propose to use higher-order statistics of local non-binarized pixel patterns for the image description. The proposed model does not require either (i) user specified quantization of the space (of pixel patterns) or (ii) any heuristics for discarding low occupancy volumes of the space. We propose to use a data driven soft quantization of the space, with parametric mixture models, combined with higher-order statistics, based on Fisher scores. We demonstrate that this leads to a more expressive representation which, when combined with discriminatively learned classifiers and metrics, achieves state-of-the-art performance on challenging texture and facial analysis datasets, in low complexity setup. Further, it is complementary to higher complexity features and when combined with them improves performance. [ABSTRACT FROM AUTHOR]

The article presents a note on the logarithmic type quantizer as a solution for the issue on controlling spacecraft attitude with quantized control torque. The quantizer which has sufficient precision and a low communication rate requirement can be chosen through the controller design parameters and aircraft's inertial matrix to check the system stability.

The Fast Fourier Transform is a very efficient algorithm for the Fourier spectrum estimation, but has the limitation of a linear frequency scale spectrum, which may not be suitable for every system. For example, audio and speech analysis needs a logarithmic frequency scale due to the characteristic of a human's ear. The Fast Fourier Transform algorithms are not able to efficiently give the desired results and modified techniques have to be used in this case. In the following text a simple technique using the Goertzel algorithm allowing the evaluation of the power spectra on an arbitrary frequency scale will be introduced. Due to its simplicity the algorithm suffers from imperfections which will be discussed and partially solved in this paper. The implementation into real systems and the impact of quantization errors appeared to be critical and have to be dealt with in special cases. The simple method dealing with the quantization error will also be introduced. Finally, the proposed method will be compared to other methods based on its computational demands and its potential speed. [ABSTRACT FROM AUTHOR]

In this paper, a blind scheme for digital video watermarking is proposed. The security of the scheme is established by using one secret key in the retrieval of the watermark. Discrete Wavelet Transform (DWT) is applied on each video frame decomposing it into a number of sub-bands. Maximum entropy blocks are selected and transformed using Principal Component Analysis (PCA). Quantization Index Modulation (QIM) is used to quantize the maximum coefficient of the PCA blocks of each sub-band. Then, the watermark is embedded into the selected suitable quantizer values. The proposed scheme is tested using a number of video sequences. Experimental results show high imperceptibility. The computed average PSNR exceeds 45 dB. Finally, the scheme is applied on two medical videos. The proposed scheme shows high robustness against several attacks such as JPEG coding, Gaussian noise addition, histogram equalization, gamma correction, and contrast adjustment in both cases of regular videos and medical videos. [ABSTRACT FROM AUTHOR]

Abstract: The core contribution of this paper is to introduce a general neat scheme based on soft vector clustering for the dithering of multidimensional signals that works in any space of arbitrary dimensionality, on arbitrary number and distribution of quantization centroids, and with a computable and controllable quantization noise. Dithering upon the digitization of one-dimensional and multi-dimensional signals disperses the quantization noise over the frequency domain which renders it less perceptible by signal processing systems including the human cognitive ones, so it has a very beneficial impact on vital domains such as communications, control, machine-learning, etc. Our extensive surveys have concluded that the published literature is missing such a neat dithering scheme. It is very desirable and insightful to visualize the behavior of our multidimensional dithering scheme; especially the dispersion of quantization noise over the frequency domain. In general, such visualization would be quite hard to achieve and perceive by the reader unless the target multidimensional signal itself is directly perceivable by humans. So, we chose to apply our multidimensional dithering scheme upon encoding true-color images – that are 3D signals – with palettes of limited sets of colors to show how it minimizes the visual distortions – esp. contouring effect – in the encoded images. [Copyright &y& Elsevier]

Niels Bohr developed hismodel of the atomic structure in 1913 that succeeded in explaining the spectral features of hydrogen atom. In the process, he incorporated some non-classical features such as discrete energy levels for the bound electrons, and quantization of their angular momenta. [ABSTRACT FROM AUTHOR]

In this section of Resonance, we invite readers to pose questions likely to be raised in a classroom situation. We may suggest strategies for dealing with them, or invite responses, or both. “Classroom” is equally a forum for raising broader issues and sharing personal experiences and viewpoints on matters related to teaching and learning science. [ABSTRACT FROM AUTHOR]

In this paper we address the optimization of the support region threshold of the μ-law companding quantizer designed for the Laplacian source of unit variance. We propose a new iterative method of determining the support region threshold, based on Newton's method. We provide a simple manner for determining the support region threshold. Numerical results show that the proposed new approach to the observed optimization problem outperforms the recently proposed method in terms of the relative error of determining the support region threshold. This indicates the usefulness of the proposed approach. [ABSTRACT FROM AUTHOR]

With the development of Internet of Things, humans with smart multimedia devices are a new trend of mobile-aware service. This new mode of awareness will inevitable brings some challenges. Among them, the quantification of social relations is the basis of mobile-aware service, and it is an abstract psychological cognitive process, involving space, time and behaviour. Therefore, using social network theory, a novel quantization and predication model with multiple decision factors is proposed, in which multiple decision factors including location, call records, service and feedback factors. These factors are incorporated to reflect the complexity and uncertainty of social relations. Also, the weight distribution is set up by information entropy, and support vector machines optimized based genetic algorithm is used to predict the social relations of mobile nodes, which overcomes the shortage of traditional method, in which the weight is set up by subjective manners and has poor dynamic adaptability. Simulation results show that, cognitive model has better predictive accuracy and dynamic adaptability. [ABSTRACT FROM AUTHOR]

In this paper a novel two-stage quantizer with the embedded G.711 quantizer is proposed for speech signal processing. The first processing stage, where the input signal is quantized with the G.711 quantizer, is followed by the second stage where the segmental uniform quantizer performs the reduction of the quantization error introduced in the first stage. In this way higher signal quality, measured by signal to quantization noise ratio, is achieved in comparison with the G.711 quantizer while no bit rate reduction is performed. Particularly, in the second stage two additional bits are introduced. Although the expected quality gain, as a result of increasing the overall bit rate for 2 bit/sample, is around 12 dB, the gain achieved with the proposed quantizer is 14 dB. This additional quality gain of 2 dB proves the advantage of the proposed two-stage quantizer. [ABSTRACT FROM AUTHOR]

Abstract: Electrocardiogram (ECG) compression can significantly reduce the storage and transmission burden for the long-term recording system and telemedicine applications. In this paper, an improved wavelet-based compression method is proposed. A discrete wavelet transform (DWT) is firstly applied to the mean removed ECG signal. DWT coefficients in a hierarchical tree order are taken as the component of a vector named tree vector (TV). Then, the TV is quantized with a vector–scalar quantizer (VSQ), which is composed of a dynamic learning vector quantizer and a uniform scalar dead-zone quantizer. The context modeling arithmetic coding is finally employed to encode those quantized coefficients from the VSQ. All tested records are selected from the Massachusetts Institute of Technology-Beth Israel Hospital arrhythmia database. Statistical results show that the compression performance of the proposed method outperforms several published compression algorithms. [Copyright &y& Elsevier]

Abstract: The method of Gaussian weighted trajectories combines the classical description of gas-phase chemical reactions and Bohr quantization of final fragment vibrations. In practice, trajectories are assigned Gaussian statistical weights such that the closer the final vibrational actions to integer values, the larger the weights. This approach, called classical trajectory method with Gaussian binning (CT-GB) in the following, is a practical implementation of classical S matrix theory (CSMT) in the random phase approximation. However, CSMT is non unitary and consequently, the most utilized version of CT-GB is not strictly normalized to unity. In other words, the sum of product and re-formed reagent state populations is not exactly equal to one. The purpose of this work is to show that normalizing these populations to unity should significantly improve the quality of the predictions for indirect reactions. This finding is illustrated from calculations on the D+ +H2 reaction. [ABSTRACT FROM AUTHOR]

Abstract: A trajectory ensemble method is introduced that enables accurate computation of microcanonical quantum reactive scattering quantities, using a classical-like simulation scheme. Individual quantum trajectories are propagated independently, using a Newton-like ODE which treats quantum dynamical effects along the reaction coordinate exactly, and preserves the phase space volume element. The sampling of initial conditions resembles a classical microcanonical simulation, but modified so as to incorporate quantization in the perpendicular mode coordinates. The method is exact for one-dimensional or separable systems, and achieves ∼1% accuracy for the coupled multidimensional benchmark applications considered here, even in the deep tunneling regime. [ABSTRACT FROM AUTHOR]

Abstract: Based on the basic principle of management entropy theory, this paper constructs a metric scale and entropy-based quantization model for evaluating the complexity of resource consolidation system engineering. Under the transformed structure of coal resource consolidation system of Shanxi Province and the constructed relation mode, the proposed model is put in practice to analyze and evaluate the complexity of Shanxi coal resources consolidation system. The results show that by importing material, energy and information, the complex system evolves to the direction of order and dynamic balance. [Copyright &y& Elsevier]

In this paper switched nonuniform and piecewise uniform scalar quantization of Laplacian source are analyzed. This scalar quantization techniques are used in order to obtain higher signal quality by increasing signal-to-quantization noise ratio (SNRQ) with respect to it's necessary robustness over a broad range of input variances in a wide range of signal volumes. We observe μ-law compandor implementation to achieve compromise between high-rate digitalization and variance adaptation. The main contribution of this model is kipping almost the same quality as the nonuniform compandor model, with simpler realization structure and the possibility of it's applying for digitalization of wide range continuous signals. [ABSTRACT FROM AUTHOR]

Copyright of Electronics & Electrical Engineering is the property of Electronics & Electrical 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.)

Abstract: This paper has proposed a planning formulation of transmission system including wind power. The risk factor is adopted to realize quantization of risk caused by the uncertainty of wind power output and loads. Using risk assessment cost as an economic index to reflect transmission programming risk, which is comparable with the network investment cost, the transmission network planning scheme can achieve both safety and economy. Emulation indicates the feasibility of this way. [Copyright &y& Elsevier]

System level analysis and design of a single-loop fourth-order sigma-delta (ΣΔ) accelerometer is presented to reduce quantization noise and enhance resolution of the micromachined accelerometer. Stability of the system is analyzed by root locus method based on the linear model established in this work. Theoretical analysis indicates that the forth-order ΣΔ micromachined accelerometer has good performance in noise, dead zone and idle tone. Based on the analysis and discussion of the system level, the transistor level design of the interface circuit is implemented, the circuit is fabricated in 0. 5 µm two poly two metal CMOS process, and the tested results indicate that the sensitivity is 1.2 V/g, nonlinearity is 0.2% , open-loop noise density is 12 µg/Hz1/2, closed-loop noise density is 80 u/Hz1/2 and the power dissipation is 40 mW. [ABSTRACT FROM AUTHOR]

A transmit antenna selection (TAS) multi-input multi-output orthogonal frequency-division multiplexing (MIMO-OFDM) system based on channel-orthogonalized space-frequency block coding (CO-SFBC) schemes was proposed for better performance. Firstly, the principles and criterions for designing CO-STBC/SFBC schemes with angle feedback were proposed, and then the effect of quantization for the feedback angle information within such schemes was discussed. Meanwhile, the TAS scheme was applied to the system to further improve the overall performance. Simulation results show that the combination of the proposed CO-STBC and TAS schemes can significantly improve the system performance, which is much larger than only applying them to systems individually. [ABSTRACT FROM AUTHOR]

Several reports published in the current issue of the journal are presented including an article on the life of Russian mathematician Vladimir I. Arnold , another on quantization of the classical orbits and on Schmallenberg virus.