Search

The significance of detecting faint and diminutive space targets cannot be overstated, as it underpins the preservation of Earth's orbital environment's safety and long-term sustainability. Founded by the different response characteristics between targets and backgrounds to aberrations, this paper proposes a novel aberration modulation correlation method (AMCM) for dim and small space target detection. By meticulously manipulating the light path using a wavefront corrector via a modulation signal, the target brightness will fluctuate periodically, while the background brightness remains essentially constant. Benefited by the strong correlation between targets' characteristic changes and the modulation signal, dim and small targets can be effectively detected. Rigorous simulations and practical experiments have validated the remarkable efficacy of AMCM. Compared to conventional algorithms, AMCM boasts a substantial enhancement in the signal-to-noise ratio (SNR) detection limit from 5 to approximately 2, with an area under the precision–recall curve of 0.9396, underscoring its ability to accurately identify targets while minimizing false positives. In essence, AMCM offers an effective method for detecting dim and small space targets and is also conveniently integrated into other passive target detection systems. [ABSTRACT FROM AUTHOR]

From a medical perspective, the 12 leads of the heart in an electrocardiogram (ECG) signal have functional dependencies with each other. Therefore, all these leads report different aspects of an arrhythmia. Their differences lie in the level of highlighting and displaying information about that arrhythmia. For example, although all leads show traces of atrial excitation, this function is more evident in lead II than in any other lead. In this article, a new model was proposed using ECG functional and structural dependencies between heart leads. In the prescreening stage, the ECG signals are segmented from the QRS point so that further analyzes can be performed on these segments in a more detailed manner. The mutual information indices were used to assess the relationship between leads. In order to calculate mutual information, the correlation between the 12 ECG leads has been calculated. The output of this step is a matrix containing all mutual information. Furthermore, to calculate the structural information of ECG signals, a capsule neural network was implemented to aid physicians in the automatic classification of cardiac arrhythmias. The architecture of this capsule neural network has been modified to perform the classification task. In the experimental results section, the proposed model was used to classify arrhythmias in ECG signals from the Chapman dataset. Numerical evaluations showed that this model has a precision of 97.02%, recall of 96.13%, F1-score of 96.57% and accuracy of 97.38%, indicating acceptable performance compared to other state-of-the-art methods. The proposed method shows an average accuracy of 2% superiority over similar works. [ABSTRACT FROM AUTHOR]

Incipient faults in interface converters can potentially lead to catastrophic failures. Detection of incipient faults contributes to proactive fault management and predictive maintenance, which effectively improves system reliability. In this paper, a detection method in correlation space is proposed to address this problem, which is based on the inherent feature of correlation changes when a fault occurs. First, a convolution process is used to weaken noise and highlight the correlation feature. Second, the current signals are transmitted to correlation space by using the Pearson correlation coefficient. Third, an accumulation and a reference compensation method are designed for enhancing the features and equalizing influence of reference adjustment. Finally, a fault detection rule is designed based on correlation features and fault excitation. Experiments on a hardware‐in‐loop(HIL) semi‐physical platform indicate that the proposed method outperforms three commonly used correlation analysis algorithms. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The significance of detecting faint and diminutive space targets cannot be overstated, as it underpins the preservation of Earth’s orbital environment’s safety and long-term sustainability. Founded by the different response characteristics between targets and backgrounds to aberrations, this paper proposes a novel aberration modulation correlation method (AMCM) for dim and small space target detection. By meticulously manipulating the light path using a wavefront corrector via a modulation signal, the target brightness will fluctuate periodically, while the background brightness remains essentially constant. Benefited by the strong correlation between targets’ characteristic changes and the modulation signal, dim and small targets can be effectively detected. Rigorous simulations and practical experiments have validated the remarkable efficacy of AMCM. Compared to conventional algorithms, AMCM boasts a substantial enhancement in the signal-to-noise ratio (SNR) detection limit from 5 to approximately 2, with an area under the precision–recall curve of 0.9396, underscoring its ability to accurately identify targets while minimizing false positives. In essence, AMCM offers an effective method for detecting dim and small space targets and is also conveniently integrated into other passive target detection systems.

Digital filtration is widely used today in many application fields, and with the increased use of low-cost embedded processors, it can be applied to vast areas. A drawback of digital filtration algorithms is the introduction of phase angle shifts in the filtered signals, thereby creating undesirable characteristics in many application fields. In this work, low-pass filters of finite impulse response and infinite impulse response types are designed with an innovative buffering scheme to delay a digitally low-passed signal by an angle ranging from 0° to 180° for real-time signals. The application of the filtration and buffering scheme on a cost-effective embedded processor with limited signal processing capabilities opens the horizons for its applicability in many signal processing fields. In assessing its practicality, the generated filtered output signal is correlated with the original signal (a low-passed version), revealing correlation values reaching 0.99 in certain instances. The novelty of the proposed approach enables its application to a broad-spectrum area of digital signal filtration. [ABSTRACT FROM AUTHOR]

Digital filtration is widely used today in many application fields, and with the increased use of low-cost embedded processors, it can be applied to vast areas. A drawback of digital filtration algorithms is the introduction of phase angle shifts in the filtered signals, thereby creating undesirable characteristics in many application fields. In this work, low-pass filters of finite impulse response and infinite impulse response types are designed with an innovative buffering scheme to delay a digitally low-passed signal by an angle ranging from 0° to 180° for real-time signals. The application of the filtration and buffering scheme on a cost-effective embedded processor with limited signal processing capabilities opens the horizons for its applicability in many signal processing fields. In assessing its practicality, the generated filtered output signal is correlated with the original signal (a low-passed version), revealing correlation values reaching 0.99 in certain instances. The novelty of the proposed approach enables its application to a broad-spectrum area of digital signal filtration.

Advanced in the present paper is an innovative approach for three-dimensional modeling of the regular relief topography formed via a ball burnishing process. The proposed methodology involves capturing a greyscale image of and profile measuring the surface topography in two perpendicular directions using a stylus method. A specially developed algorithm further identifies the best match between the measured profile segment and a row or column from the captured topography image by carrying out a signal correlation assessment based on an appropriate similarity metric. To ensure accurate scaling, the image pixel grey levels are scaled with a factor calculated as being the larger ratio between the ultimate heights of the measured profilograms and the more perfectly matched image row/column. Nine different similarity metrics were tested to determine the best performing model. The developed approach was evaluated for eight distinct types of fully and partially regular reliefs, and the results reveal that the best-scaled 3D topography models are produced for the fully regular reliefs with much greater heights. Following a thorough analysis of the results obtained, at the end of the paper, we draw some conclusions and discuss potential future work. [ABSTRACT FROM AUTHOR]

Changes in arousal influence cortical sensory representations, but the synaptic mechanisms underlying arousal-dependent modulation of cortical processing are unclear. Here, we use 2-photon Ca2+ imaging in the auditory cortex of awake mice to show that heightened arousal, as indexed by pupil diameter, broadens frequency-tuned activity of layer 2/3 (L2/3) pyramidal cells. Sensory representations are less sparse, and the tuning of nearby cells more similar when arousal increases. Despite the reduction in selectivity, frequency discrimination by cell ensembles improves due to a decrease in shared trial-to-trial variability. In vivo whole-cell recordings reveal that mechanisms contributing to the effects of arousal on sensory representations include state-dependent modulation of membrane potential dynamics, spontaneous firing, and tone-evoked synaptic potentials. Surprisingly, changes in short-latency tone-evoked excitatory input cannot explain the effects of arousal on the broadness of frequency-tuned output. However, we show that arousal strongly modulates a slow tone-evoked suppression of recurrent excitation underlying lateral inhibition [H. K. Kato, S. K. Asinof, J. S. Isaacson, Neuron, 95, 412-423, (2017)]. This arousal-dependent "network suppression" gates the duration of tone-evoked responses and regulates the broadness of frequency tuning. Thus, arousal can shape tuning via modulation of indirect changes in recurrent network activity.

Advanced in the present paper is an innovative approach for three-dimensional modeling of the regular relief topography formed via a ball burnishing process. The proposed methodology involves capturing a greyscale image of and profile measuring the surface topography in two perpendicular directions using a stylus method. A specially developed algorithm further identifies the best match between the measured profile segment and a row or column from the captured topography image by carrying out a signal correlation assessment based on an appropriate similarity metric. To ensure accurate scaling, the image pixel grey levels are scaled with a factor calculated as being the larger ratio between the ultimate heights of the measured profilograms and the more perfectly matched image row/column. Nine different similarity metrics were tested to determine the best performing model. The developed approach was evaluated for eight distinct types of fully and partially regular reliefs, and the results reveal that the best-scaled 3D topography models are produced for the fully regular reliefs with much greater heights. Following a thorough analysis of the results obtained, at the end of the paper, we draw some conclusions and discuss potential future work.

Noise correlations (r(noise)) between neurons can affect a neural population's discrimination capacity, even without changes in mean firing rates of neurons. r(noise), the degree to which the response variability of a pair of neurons is correlated, has been shown to change with attention with most reports showing a reduction in r(noise). However, the effect of reducing r(noise) on sensory discrimination depends on many factors, including the tuning similarity, or tuning correlation (r(tuning)), between the pair. Theoretically, reducing r(noise) should enhance sensory discrimination when the pair exhibits similar tuning, but should impair discrimination when tuning is dissimilar. We recorded from pairs of neurons in primary auditory cortex (A1) under two conditions: while rhesus macaque monkeys (Macaca mulatta) actively performed a threshold amplitude modulation (AM) detection task and while they sat passively awake. We report that, for pairs with similar AM tuning, average r(noise) in A1 decreases when the animal performs the AM detection task compared with when sitting passively. For pairs with dissimilar tuning, the average r(noise) did not significantly change between conditions. This suggests that attention-related modulation can target selective subcircuits to decorrelate noise. These results demonstrate that engagement in an auditory task enhances population coding in primary auditory cortex by selectively reducing deleterious r(noise) and leaving beneficial r(noise) intact.

Correlation estimation between echo signal and leakage signal is indispensable when designing transceiver distance or processing leakage signal in frequency modulated continuous wave (FMCW) radar system. Although many contributions investigate methods for correlation estimation of leakage signal, almost all of them consider a random process and are difficult to quantify the relation. Differently, in this brief, we propose a correlation estimation method utilizing information geometry theory to explore a certain condition that makes the correlation degree of leakage signal and echo signal least. Through this method, the random issue of estimation in signals correlation calculation process could be transformed into a deterministic issue. The validity of proposed method is proved by both simulation and measurement results. The optimal correlation condition, determined conveniently by our proposed method, will benefit for antennas distance design and future signal processing to cancel leakage signal. [ABSTRACT FROM AUTHOR]

Array gain (AG) is significant in evaluating the detection performance of the vertical line array, which is directly determined by the correlation of signal and noise, respectively. In this paper, we analyze the vertical correlation for a 16-element vertical line array experimented in the deep ocean in 2016. The ray interference theory is utilized to interpret the mechanism of the vertical correlation of the sound field in different zones. In the direct-arrival zone, the direct rays and once-surface-reflected rays are two dominated components, whose arrival time difference for each element are nearly the same, and the vertical correlation is high. In the shadow zone, the sound field is mainly dominated by bottom-reflected rays and the vertical correlation decreases due to different grazing angles and arrival times of each ray. Different from the previous assumption of noise independence, the effect of noise correlation on the AG is analyzed through the measured marine environmental noise. Results indicate that the noise correlation coefficients in two zones are low but not 0. In the direct-arrival zone, AG is about 10 dB, very close to the ideal value of 10 log M . AG even exceeds it when NG is negative. Moreover, AG in the direct-arrival zone is higher than the one in the shadow zone. [ABSTRACT FROM AUTHOR]

Changes in arousal influence cortical sensory representations, but the synaptic mechanisms underlying arousal-dependent modulation of cortical processing are unclear. Here, we use 2-photon Ca2+ imaging in the auditory cortex of awake mice to show that heightened arousal, as indexed by pupil diameter, broadens frequency-tuned activity of layer 2/3 (L2/3) pyramidal cells. Sensory representations are less sparse, and the tuning of nearby cells more similar when arousal increases. Despite the reduction in selectivity, frequency discrimination by cell ensembles improves due to a decrease in shared trial-to-trial variability. In vivo whole-cell recordings reveal that mechanisms contributing to the effects of arousal on sensory representations include state-dependent modulation of membrane potential dynamics, spontaneous firing, and tone-evoked synaptic potentials. Surprisingly, changes in short-latency tone-evoked excitatory input cannot explain the effects of arousal on the broadness of frequency-tuned output. However, we show that arousal strongly modulates a slow tone-evoked suppression of recurrent excitation underlying lateral inhibition [H. K. Kato, S. K. Asinof, J. S. Isaacson, Neuron, 95, 412-423, (2017)]. This arousal-dependent "network suppression" gates the duration of tone-evoked responses and regulates the broadness of frequency tuning. Thus, arousal can shape tuning via modulation of indirect changes in recurrent network activity. [ABSTRACT FROM AUTHOR]

In order to solve the problem of peak-to-average power ratio of optical orthogonal frequency division multiplexing system, a partial transmission sequence algorithm based on correlation analysis is proposed. By analyzing the correlation among the alternative signals, the algorithm classifies the strong correlation signal and the weak correlation signal, and searches the strong correlation signal selectively and the weak correlation signal completely, thus reducing the searching times on the whole. In addition, this paper optimizes the phase factor weighting process by analyzing the relationship between alternative phase factor sequences. The simulation results show that the peak-to-average power ratio of the system can be improved effectively under the three segmentation states. Especially in the interleaved segmentation state, the proposed algorithm is compared with the traditional partial transmission sequence algorithm. The proposed algorithm is with no-performance loss of peak-to-average power ratio, and the computational complexity is greatly reduced. [ABSTRACT FROM AUTHOR]

This paper presents a method based on signal correlation to detect delamination defects of widely used carbon fiber reinforced plastic with high precision and a convenient process. The objective of it consists in distinguishing defect and non-defect signals and presenting the depth and size of defects by image. A necessary reference signal is generated from the non-defect area by using autocorrelation theory firstly. Through the correlation calculation results, the defect signal and non-defect signal are distinguished by using Euclidean distance. In order to get more accurate time-of-flight, cubic spline interpolation is introduced. In practical automatic ultrasonic A-scan signal processing, signal correlation provide a new way to avoid problems such as signal peak tracking and complex gate setting. Finally, the detection results of a carbon fiber laminate with artificial delamination through ultrasonic phased array C-scan acquired from Olympus OmniScan MX2 and this proposed algorithm are compared, which showing that this proposed algorithm performs well in defect shape presentation and location calculation. The experiment shows that the defect size error is less than 4%, the depth error less than 3%. Compared with ultrasonic C-scan method, this proposed method needs less inspector’s prior-knowledge, which can lead to advantages in automatic ultrasonic testing.

Array gain (AG) is significant in evaluating the detection performance of the vertical line array, which is directly determined by the correlation of signal and noise, respectively. In this paper, we analyze the vertical correlation for a 16-element vertical line array experimented in the deep ocean in 2016. The ray interference theory is utilized to interpret the mechanism of the vertical correlation of the sound field in different zones. In the direct-arrival zone, the direct rays and once-surface-reflected rays are two dominated components, whose arrival time difference for each element are nearly the same, and the vertical correlation is high. In the shadow zone, the sound field is mainly dominated by bottom-reflected rays and the vertical correlation decreases due to different grazing angles and arrival times of each ray. Different from the previous assumption of noise independence, the effect of noise correlation on the AG is analyzed through the measured marine environmental noise. Results indicate that the noise correlation coefficients in two zones are low but not 0. In the direct-arrival zone, AG is about 10 dB, very close to the ideal value of 10 log M . AG even exceeds it when NG is negative. Moreover, AG in the direct-arrival zone is higher than the one in the shadow zone.

Abstract This paper introduces a new combined technique for wind turbine islanding detection using the trajectory of state variables and wavelet transform in microgrid system. The proposed relay is utilized of energy variation state of time-frequency transform coefficients of local signals in two-dimensional space. In order to improve of the proposed relay performance, a signal selection method based on the correlation concept between islanding and non-islanding signals. From of all patterns, the best of them with high correlation in islanding status is selected for the proposed relay learning. A neuro-fuzzy machine is used as learning of selected patterns to avoid threshold selection. The proposed technique is utilized to wind turbine islanding detection in a microgrid system contains various types of distributed generation including wind turbine, Combined Heat and Power (CHP) and photovoltaic system. Many islanding and non-islanding situation including motor starting, various load and capacitor switching in various operation conditions in the studied microgrid are simulated. Millstone characteristics of the proposed technique are included passive-based technique, negligible None Detection Zone (NDZ), suitable for microgrid application, performance increment in detection and fast detection time. Operation results of the proposed relay in various conditions confirm the performance of the proposed detection relay. Highlights • Negligible None detection Zone. • Avoiding of threshold selection. • Suitable for microgrid application. • Usable in noisy condition. • Best data selection method. [ABSTRACT FROM AUTHOR]

Horizontal 4 mm-thickness cracks with various depth in different cement mortar specimens simulate respectively various inner micro-defects. GPR antenna of 1.0 GHz and 2.3 GHz central frequency scans respectively the inner-cracked specimens and non-crack one. Electromagnetic waveform characteristic, travel time and correlation of encoded ground penetrating radar reflection signals are quantitatively evaluated. The electromagnetic waveform and its travel time from 2.3 GHz antenna appear distinct reflection characteristic at the interface of inner crack; while only transmission of electromagnetic wave is observed when 1.0 GHz antenna employed. The correlation coefficient of encoded signals, is an available parameter to depict quantitatively inner crack, based on which a brief method to visualize inner crack is promoted within average erroneous percentage of 6% in shallow crack when scanned by 2.3 GHz antenna. [ABSTRACT FROM AUTHOR]

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.)

In this paper, a model is presented to simulate wave propagation in indoor corridors and tunnels with imperfectly conducting walls. The model is based on the waveguiding effect of corridors and tunnels. This approach is based on assuming that the boundaries of the waveguide section are constant impedance surface as the surface impedance of the wall is almost independent of the angle of the wave incidence onto the wall. An analytical approach for the calculation of the signal correlation between the transmitters and receivers elements in tunnels and indoor corridors is proposed. A new approach for determining the best locations of the indoor access points is introduced based on minimum correlation between sources with minimum cross talk. A scenario is considered in order to check the accuracy of this model. This scenario is verified by comparing experimental and numerical simulation results. Good agreement is achieved. [ABSTRACT FROM AUTHOR]

Wireless networks are propelled to improve the network throughput effectively to face the challenge of sustaining the rapid growth of data traffic and the high density of wireless nodes. Exposed terminals are a main source in wireless networks that degrades the network throughput performance through excessively avoiding interferences and forbidding concurrencies. To combat the exposed terminal problem and exploit the concurrent transmissions in wireless networks, we present the design of Interference Resistant Multiple Access (IRMA) in this paper, which can achieve higher throughput compared to the 802.11 standard. By observing that nodes in current protocols waste transmission opportunities in two different scenarios, IRMA exploits the concurrency in two aspects. IRMA proposes a signature detection method in the physical layer to combat control frames’ collisions, thus exploits the concurrency at the transmitter side. IRMA also designs a new NAV update scheme in the MAC layer to differentiate the interference ranges of different transmission links, thus exploits the concurrency of all non-interfering links. Experimental results based on USRP2 demonstrate the feasibility of the signature detection method, and simulations based on ns-2 show that IRMA outperforms the 802.11 standard and other protocols significantly. [ABSTRACT FROM AUTHOR]

To study the spatiotemporal dynamics of neural activity in a cortical population, we implanted a 10 × 10 microelectrode array in the vibrissal cortex of urethane-anesthetized rats. We recorded spontaneous neuronal activity as well as activity evoked in response to sustained and brief sensory stimulation. To quantify the temporal dynamics of activity, we computed the probability distribution function (PDF) of spiking on one electrode given the observation of a spike on another. The spike-triggered PDFs quantified the strength, temporal delay, and temporal precision of correlated activity across electrodes. Nearby cells showed higher levels of correlation at short delays, whereas distant cells showed lower levels of correlation, which tended to occur at longer delays. We found that functional space built based on the strength of pairwise correlations predicted the anatomical arrangement of electrodes. Moreover, the correlation profile of electrode pairs during spontaneous activity predicted the "signal" and "noise" correlations during sensory stimulation. Finally, mutual information analyses revealed that neurons with stronger correlations to the network during spontaneous activity, conveyed higher information about the sensory stimuli in their evoked response. Given the 400-μm-distance between adjacent electrodes, our functional quantifications unravel the spatiotemporal dynamics of activity among nearby and distant cortical columns. [ABSTRACT FROM AUTHOR]

• The drill string vibration signals are obtained by the sensors with a three-axis accelerometer and a gyroscope. • Supervised machine learning is used to establish a classification model of vibration patterns. • Through the application of classification model in the actual drill data, the specific vibration types of various modes are clarified, which proves that the model can effectively distinguish different vibration modes and its accuracy can reach up to 95%. Vibration signal measurement is one of the important methods to study the movement mode of the drill string. Through the interpretation of the vibration signal, the vibration pattern of the drill string can be accurately identified. MWD is a measurement method which can more directly reflect the vibration information of the drill string. In this paper, firstly, the drill string vibration signal is obtained by the sensors with a three-axis accelerometer and a gyroscope, and the sensor's response has been solved and analyzed, which proves the effectiveness of this method for expressing drill string vibration information and the correlation between the measured signals. Then, the correlation coefficient, as the characteristic information basing on signal combination, is proposed; since the correlation coefficients of different patterns have different distribution characteristics, supervised machine learning is used to establish a classification model of vibration patterns. Finally, through the application of classification model in the actual drill data, the specific vibration types of various modes are clarified, which proves that the classification model can effectively distinguish different vibration modes and its accuracy can reach up to 95%. [ABSTRACT FROM AUTHOR]

Covariance-based detection is a low-complexity blind spectrum sensing scheme that exploits spatial and/or temporal correlations of primary signals. However, its performance severely degrades with the decrease of signal correlations. In this work, a weighted-covariance-based detector is proposed by introducing data-aided weights to the covariance matrix. The false alarm probability, decision threshold, and detection probability are analyzed in the low signal-to-noise ratio (SNR) regime, and their approximate analytical expressions are derived based on the central limit theorem. The analyses are verified through simulations. Experiments with simulated multiple-antenna signals and field measurement digital television signals show that the proposed weighted detection can significantly outperform the original covariance-based detection. [ABSTRACT FROM AUTHOR]

Since its discovery nearly four decades ago, sequential microelectrode mapping using hundreds of recording sites has been able to reveal a precise tonotopic organization of the auditory cortex. Despite concerns regarding the effects that anesthesia might have on neuronal responses to tones, anesthesia was essential for these experiments because such dense mapping was elaborate and time-consuming. Here, taking an 'all-at-once' approach, we investigated how isoflurane modifies spatiotemporal activities by using a dense microelectrode array. The array covered the entire auditory cortex in rats, including the core and belt cortices. By comparing neuronal activity in the awake state with activity under isoflurane anesthesia, we made four observations. First, isoflurane anesthesia did not modify the tonotopic topography within the auditory cortex. Second, in terms of general response properties, isoflurane anesthesia decreased the number of active single units and increased their response onset latency. Third, in terms of tuning properties, isoflurane anesthesia shifted the response threshold without changing the shape of the frequency response area and decreased the response quality. Fourth, in terms of population activities, isoflurane anesthesia increased the noise correlations in discharges and phase synchrony in local field potential ( LFP) oscillations, suggesting that the anesthesia made neuronal activities redundant at both single-unit and LFP levels. Thus, while isoflurane anesthesia had little effect on the tonotopic topography, its profound effects on neuronal activities decreased the encoding capacity of the auditory cortex. [ABSTRACT FROM AUTHOR]

An improved subband noise reduction technique is proposed for two‐microphone voice communication systems. The technique aims to enhance the speech quality by utilising a subband structure with different noise reduction schemes for different frequency bands. In the low‐frequency band where dominant cues of speech spectral components are usually located and the noise signals from the two channels are mainly correlated, the spectral subtraction method, together with a new variable noise subtraction parameter, is employed so that the noise attenuation performance and speech distortion are controllable. In the high‐frequency band where less‐dominant frequency information of speech spectrum is located, the modified cross‐spectral subtraction technique is utilised to remove the high‐frequency decorrelated noise spectral components. Extensive comparisons among various noise reduction techniques based on computer simulations demonstrate that the proposed two‐microphone subband noise reduction scheme achieves excellent noise attenuation performance while preserving the speech quality. [ABSTRACT FROM AUTHOR]

This article presents the application of a signal correlation technique to automatically classify ultrasonic A-scan signals for defect and defect-free regions in isotropic and anisotropic materials. First, feature extraction was implemented by generating a reference A-scan signal of a defect-free area using an autocorrelation function and statistics. Then, a cross-correlation function, utilized as a feature detector, was applied to the reference signal and a signal of interest (SOI) to detect defect-free features in an SOI. The correlation result was considered as a pattern containing both defect and defect-free features. Next, the pattern was classified by measuring the similarity between features of the reference signal and an SOI based on their Euclidean distance. Each A-scan signal classification result was then plotted on a 2D map based on its position on the specimen. The present work uses multiple correlation functions and statistics to classify defect signals rather than relying on an inspector’s prior knowledge to interpret C-scan data, and has particular value in automated ultrasonic signal classification and characterization. [ABSTRACT FROM AUTHOR]

Due to high attenuation and large path loss, it is usually very difficult to measure the channel characteristics of the plasma sheath from the received signal. This paper proposes a novel method to measure them from the reflected signal. Using the finite-difference time-domain algorithm, electron density variation of the plasma sheath and its impact on the transmitted and reflected signals are investigated numerically. High correlations between these two signals are observed from both amplitude and phase, which enables us to online estimate one signal from the other for channel measurement and channel modeling conveniently. This would be very useful to further develop some channel adaptive communication techniques for alleviating the radio blackout problem. [ABSTRACT FROM PUBLISHER]