A massively parallel signal and image processing architecture is considered. The architecture is comprised of 2D arrays of cells that simulate the response of retina neurons. The results of simulations are compared to...
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ISBN:
(纸本)0819416207
A massively parallel signal and image processing architecture is considered. The architecture is comprised of 2D arrays of cells that simulate the response of retina neurons. The results of simulations are compared to previously published experimental results and the system is applied to detection of spatio-temporal features in sequences of images representative of pulse- doppler radar images. By arranging the output layer so that the cells respond to various key input features an array of feature extraction cells can be obtained. The system is characterized by developing an image space to feature space mapping.
We compare the modified Wigner distribution functions obtained via the Choi-Williams kernel and its rotation, as well as by the tilted Gaussian kernel. Based on several commonly used examples, we demonstrate that the ...
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ISBN:
(纸本)0819406945
We compare the modified Wigner distribution functions obtained via the Choi-Williams kernel and its rotation, as well as by the tilted Gaussian kernel. Based on several commonly used examples, we demonstrate that the modified Wigner distribution obtained via the Gaussian kernel can minimize the artifacts more effectively and has the capability of selectively filtering out undesired components.
A multiresolution model of a discrete fractional Brownian motion is developed. The model leads to a multiscale algorithm for constructing the optimal filter that must be used in detection problems involving a fraction...
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We propose a scale-limited signal model based on wavelet representation and study the reconstructability of scale-limited signals via extrapolation in this research. In analogy with the band-limited case, we define a ...
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ISBN:
(纸本)0819416207
We propose a scale-limited signal model based on wavelet representation and study the reconstructability of scale-limited signals via extrapolation in this research. In analogy with the band-limited case, we define a scale-limited time-concentrated operator, and examine various vector spaces associated with such an operator. It is proved that the scale-limited signal space can be decomposed into the direct sum of two subspaces and only the component in one subspace can be exactly reconstructed, where the reconstructable subspace can be interpreted as a space consisting of scale/time-limited signals. Due to the ill-posedness of scale-limited extrapolation, a regularization process is introduced for noisy data extrapolation.
The idea is (i) to use a variable energy allocation per signaling symbol and (ii) to pseudorandomize the order in which signaling symbols are transmitted. This strategy will allow the most important part of the sensor...
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The idea is (i) to use a variable energy allocation per signaling symbol and (ii) to pseudorandomize the order in which signaling symbols are transmitted. This strategy will allow the most important part of the sensor data to be (i) decorrelated against periodic unequal power interfering noise and specifically (ii) where that noise is purposely tailored or allocated in an attempt to provide maximum disruption of information transport as in 'smart' jamming. In a very real sense, perfect compression followed by this method leads to a genre of spread spectrum known as Time Hopping (TH).
In many applications (radar, communication, plasma physics) the signal of interest is sinusoidal and is hidden in non-white noise. The multi-window method of spectrum estimation gives a constant false alarm test for t...
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ISBN:
(纸本)0819406945
In many applications (radar, communication, plasma physics) the signal of interest is sinusoidal and is hidden in non-white noise. The multi-window method of spectrum estimation gives a constant false alarm test for the presence of a sinusoid in a time series if the noise can be assumed Gaussian. In this paper we generalize the method to an array and study the resulting test. Expressions for the probabilities of detection and of false alarm are obtained analytically and receiver operation characteristic curves are computed for a particular scenario under different conditions.
A digital audio watermarking scheme of low complexity is proposed in this research as an effective way to deter users from misusing or illegally distributing audio data. Previous work on audio watermarking has primari...
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A digital audio watermarking scheme of low complexity is proposed in this research as an effective way to deter users from misusing or illegally distributing audio data. Previous work on audio watermarking has primarily focused on the inaudibility of the embedded watermark and its robustness against attacks such as compression and noise. In this research, special attention is paid to the synchronization attack caused by casual audio editing or malicious random cropping, which is a low-cost yet effective attack to watermarking algorithms developed before. The proposed scheme is based on audio content analysis and watermark embedding in the Fourier transform domain. A blind watermark detection technique is developed to identify the embedded watermark under various types of attacks.
Distributed sensor networks have been proposed for a wide range of applications. In this paper, our goal is to locate a wideband source, generating both acoustic and seismic signals, using both seismic and acoustic se...
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Distributed sensor networks have been proposed for a wide range of applications. In this paper, our goal is to locate a wideband source, generating both acoustic and seismic signals, using both seismic and acoustic sensors. For a far-field acoustic source, only the direction-of-arrival (DOA) in the coordinate system of the sensors is observable. We use the approximate Maximum-Likelihood (AML) method for DOA estimations from several acoustic arrays. For a seismic source, we use data collected at a single tri-axial accelerometer to perform DOA estimation. Two seismic DOA estimation methods, the eigen-decomposition of the sample covariance matrix method and the surface wave method are used. Field measurements of acoustic and seismic signals generated by vertically striking a heavy metal plate placed on the ground in an open field are collected. Each acoustic array uses four low-cost microphones placed in a square configuration and separated by one meter. The microphone outputs of each array are collected by a synchronized A/D recording system and processed locally based on the AML algorithm for DOA estimation. An array of six tri-axial accelerometers arranged in two rows whose outputs are fed into an ultra low power and high resolution network-aware seismic recording system. Field measured data from the acoustic and seismic arrays show the estimated DOAs and consequent localizations of the source are quite accurate and useful. Beamforming, Source localization,.
CORDIC algorithms offer an attractive alternative to multiply-and-add based algorithms for the implementation of two-dimensional rotations, preserving either norm: (x2 + y2) 1/2 or (x2 - y2) 1/2 . Indeed these nor who...
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CORDIC algorithms offer an attractive alternative to multiply-and-add based algorithms for the implementation of two-dimensional rotations, preserving either norm: (x2 + y2) 1/2 or (x2 - y2) 1/2 . Indeed these nor whose computation is a significant part of the evaluation of the two-dimensional rotations, are computed much more easily by the CORDIC algorithms. However the part played by norm computations in the evaluation of rotations becomes quickly small as the dimension of the space increases. Thus, in spaces of dimension 5 or more, there is no practical alternative to multiply-and-add based algorithms. In the intermediate region, dimensions 3 and 4, extensions of the CORDIC algorithms are an interesting option. The four-dimensional extensions are particularly elegant and are the main object of this paper.
Following a brief discussion of the potential relevance of chaotic noise models, we consider the problem of separating a signal from an additive mixture with nonlinear noise. The approach we take exploits various prop...
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ISBN:
(纸本)0819416207
Following a brief discussion of the potential relevance of chaotic noise models, we consider the problem of separating a signal from an additive mixture with nonlinear noise. The approach we take exploits various properties of linear filters: their linearity is, of course, important when dealing with additive mixtures of signals, but we also need to understand their effect on nonlinear processes. We describe how FIR and IIR filters differ radically in this respect, and discuss the ways in which each can be used in conjunction with various nonlinear transformations for signal separation.
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