The compression of digital video data has many applications in the transmission and storage of video sequences. For moderate compression ratios there are many techniques which can provide satisfactory performance. For...
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The compression of digital video data has many applications in the transmission and storage of video sequences. For moderate compression ratios there are many techniques which can provide satisfactory performance. For high compression ratios, however, typical compression techniques produce noticeable artifacts in the reconstructed video. This paper proposes a technique for the post-processing of motion-compensated compressed video data. The technique utilizes a stochastic regularization approach which can be realized using a simple and fast iterative computational algorithm. The approach has been applied to the post-processing of color video sequences and yields good results.
Based on the criterion of maximizing signal to noise ratio (SNR), the optimum matched filter is, in general, the solution to a real integral equation. With regards to the detection of narrowband, bandpass signals, we ...
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Based on the criterion of maximizing signal to noise ratio (SNR), the optimum matched filter is, in general, the solution to a real integral equation. With regards to the detection of narrowband, bandpass signals, we present the full form of the integral equation based upon complex envelopes. The correct form of the integral equation includes a complementary or pseudo-autocorrelation function which can be ignored for most matched filtering applications. However, in the presence of improper complex noise, overlooking the function leads to a "non-optimal" matched filter. To illustrate the concept, we apply the theory to a simple direct-sequence code-division multiple-access (DS-CDMA) system.
We present a connection between the discrete Gabor expansion and the evolutionary spectral theory. Including a scale parameter in the Gabor expansion, we obtain a new representation for deterministic signals that is a...
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We present a connection between the discrete Gabor expansion and the evolutionary spectral theory. Including a scale parameter in the Gabor expansion, we obtain a new representation for deterministic signals that is analogous to the Wold-Cramer decomposition for non-stationary processes. The energy distribution resulting from the expansion is easily calculated from the Gabor coefficients. By choosing Gaussian windows and appropriate scales, the expansion can represent narrow-band and wide-band signals, as well as their combination. As an application, we consider the masking of signals in the time-frequency space and provide an approximate implementation using the new Gabor expansion. Examples illustrating the time-frequency analysis and the masking are given.
We describe a methodology for a systematic approach to the processing of measurements of electrical potentials which originate in cardiac electrical activity. This methodology can be seen as an imaging modality whose ...
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We describe a methodology for a systematic approach to the processing of measurements of electrical potentials which originate in cardiac electrical activity. This methodology can be seen as an imaging modality whose goal is the display and interpretation of an image of the electrical activity of the heart. It requires the display and analysis of electric field data as a function of time and space on complex, irregular three-dimensional geometries. This imaging modality does not reconstruct anatomy, but rather it uses an anatomical model as a basis with which to analyze physical quantities originating in the heart. The goals of this analysis are to achieve a better understanding of normal and abnormal electrical activity of the heart and to apply this knowledge to the diagnosis and monitoring of patients.< >
The design of efficient parallel processing implementations for speeding up the computationally intensive estimation of higher order statistics (HOS) has been recognized as an important task by the signalprocessing c...
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The design of efficient parallel processing implementations for speeding up the computationally intensive estimation of higher order statistics (HOS) has been recognized as an important task by the signalprocessing community. We report on the synthesis of minimum running time (latency) data-parallel algorithms that can be employed to compute all moment lags, up to the 3rd or 4th-order, on the MasPar-1 single instruction multiple data (SIMD) parallel system. By construction the synthesized SIMD algorithms require constant memory per processing element (PE), thus allowing the processing of 1-D input data sequences with as many as M=2/sup 10/ data samples. Simulation results are presented showing the gain in speedup and execution times, as compared to optimized versions of the serial estimation algorithm running in powerful workstations.
A stochastic gradient-based decorrelation algorithm is suggested for separation of an unknown linear mixture of signals. It is shown that while the decorrelation algorithm is similar in cost to the LMS algorithm, its ...
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A stochastic gradient-based decorrelation algorithm is suggested for separation of an unknown linear mixture of signals. It is shown that while the decorrelation algorithm is similar in cost to the LMS algorithm, its rate of convergence is significantly faster, making it more attractive for signal separation. Analysis of the decorrelator algorithm shows that the faster speed of convergence is a consequence of the eigenvalue spread associated with the decorrelation problem, which is smaller than the spread associated with the corresponding mean square problem. Operation of the algorithm is illustrated as an adaptive multiuser detector in a multiple carrier CDMA system.
Vast research was recently performed on signal detection of multiuser code division multiple access (CDMA). Particularly for uplink (users to base station) the signals are asynchronous and the near-far problem is an i...
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Vast research was recently performed on signal detection of multiuser code division multiple access (CDMA). Particularly for uplink (users to base station) the signals are asynchronous and the near-far problem is an important issue to deal with. All near-far resistant detectors, adaptive or non-adaptive, assume knowledge of the relative delays of the different users signals. Among these are the one-shot detectors suggested by Verdu. In this paper we suggest an adaptive algorithm to decorrelate the outputs of the one shot matched filters that assumes no knowledge of the relative delay. The performance of this approach is shown to be better than the non-adaptive "zero-forcing" method previously used and which implements linear transformation via the inverse of matched filters output cross-correlation. For simplicity a two-user case is presented. Extension to a higher number of users is relatively simple.
Using a one-shot matched filter followed by a decorrelating detector, results in outputs corresponding to the main user and the left (earlier bit) and right (current bit) portion of the code of the other users. Due to...
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Using a one-shot matched filter followed by a decorrelating detector, results in outputs corresponding to the main user and the left (earlier bit) and right (current bit) portion of the code of the other users. Due to reduced power, these outputs will result in a degradated probability of error. The purpose of this paper is to propose a method of combining for the data of the split code users. We suggest to use combining gain in proportion to the relative user delays. The resulting decorrelating detector always performs better than the split-output detector. Such diversity data combining eliminates the need for the multiple one-shot filters, one for each user.
In ATM networks, the purpose of connection admission control is to decide if allowing a new connection into the network violates a quality of service measure, such as the cell loss probability. Testing the algorithms ...
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In ATM networks, the purpose of connection admission control is to decide if allowing a new connection into the network violates a quality of service measure, such as the cell loss probability. Testing the algorithms that perform connection admission control is difficult because of the complexity of the ATM switches, the low cell loss probabilities required by ATM networks, and the unwieldiness of matching statistical models of the traffic entering the network to the connection traffic descriptors used by the call admission control algorithm. In the paper, instead of using statistical traffic models, the authors describe the traffic entering the network by the connection traffic descriptors standardised by the ATM Forum. They develop a simulation model for estimating the cell loss probability, derive upper and lower bounds on the cell loss probability, use importance sampling to increase the efficiency of the simulation, and find an analytical solution for the improvement in simulation efficiency. For the examples considered they obtained 3 to 9 orders of magnitude improvement in efficiency compared to conventional Monte Carlo simulation.
Adaptive antenna arrays are applied at the base station to improve performance of a mobile communication system operating in a flat slowly fading Rayleigh channel. Analytical expressions are derived for the average pr...
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Adaptive antenna arrays are applied at the base station to improve performance of a mobile communication system operating in a flat slowly fading Rayleigh channel. Analytical expressions are derived for the average probability of error of the sample matrix inversion (SMI) and an eigenanalysis-based method for the case of a single co-channel interference. It is shown that the eigenanalysis-method is superior to the SMI method when the array covariance matrix is estimated from small data sets. The analysis is supported by numerical results obtained from simulations.
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