A multiprocessor scheduler has been developed for scheduling signalprocessing and other algorithms on programmable digital signal processors that can be connected in a common-bus or hypercube topology. The scheduler ...
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A multiprocessor scheduler has been developed for scheduling signalprocessing and other algorithms on programmable digital signal processors that can be connected in a common-bus or hypercube topology. The scheduler requires an acyclic precedence graph of the algorithm and the cost of all interprocessor communications. The software tool permits the user to select from among three different scheduling algorithms. The first is a heuristic method, the second uses dynamic programming, and the third uses integer linear programming. Schedules for six practical signal processing algorithms are obtained, and throughput rates are compared to those obtained with uniprocessor implementation.< >
The paper presents new systems of orthogonal basic functions for fast signal processing algorithms, which can be used in different types of radars. The functional systems suggested allow us to use fast Fourier transfo...
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The paper presents new systems of orthogonal basic functions for fast signal processing algorithms, which can be used in different types of radars. The functional systems suggested allow us to use fast Fourier transform for calculating the convolution and the correlation function. The results were tested with the help of Monte-Carlo simulation as well as the physical radar model
Some results on the study of algebraic methods for the analysis and design of time-frequency signal processing algorithms are presented. A time-frequency signal is defined as a signal whose spectral characteristics va...
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Some results on the study of algebraic methods for the analysis and design of time-frequency signal processing algorithms are presented. A time-frequency signal is defined as a signal whose spectral characteristics vary with time. Time-frequency signalprocessing is the mathematical treatment of signals with the objective of extracting relevant information. The processing of time-frequency signals is accomplished through the development of suitable algorithms. Emphasis placed on the analysis, design, and modification of time-frequency algorithms for machine implementation, and on the development of an environment to assist on this implementation. This environment is termed a computational mathematics environment (CME).< >
Significant advances have been made in recent years in the development of digital signalprocessing (DSP) algorithms and their exploitation in computational electromagnetics. In the widest sense, one could include in ...
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Significant advances have been made in recent years in the development of digital signalprocessing (DSP) algorithms and their exploitation in computational electromagnetics. In the widest sense, one could include in this category various techniques such as neural networks, genetic algorithms etc. In this paper, we focus however in reviewing the application of signalprocessing techniques to solve particular EMC problems. Two specific problems are addressed. First, the use of modal expansion techniques (MET) is described as applied to the interfacing of thin wires to large electromagnetic models described by a coarse mesh. MET allows accurate placement and description of thin wires irrespective of the mesh spatial resolution. Second, the use of digital filtering interface (DPI) is discussed as applied to the description in time-domain models of general material properties and other features with frequency-dependent properties. It is shown that advanced signalprocessing techniques can increase substantially the accuracy and efficiency of numerical solvers.
This paper is dealing with the implementation of the signal processing algorithms, specifically the Fast Fourier Transform and the matrix multiplication, using the new tool for mapping instructions on functional units...
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This paper is dealing with the implementation of the signal processing algorithms, specifically the Fast Fourier Transform and the matrix multiplication, using the new tool for mapping instructions on functional units of the processor. The tool is using the signal-flow based description of the algorithm instead of the sequential notation of the program execution. The selected target processor is a multi-core digital signal processor based on the very long instruction word architecture. The final assembly code is analyzed in terms of utilization of the functional units and general purpose registers.
Using oversampled sigma-delta (/spl Sigma/-/spl Delta/) techniques a signal can be represented as a single bit binary data stream ({-1, 1}), with the quantization noise high pass filtered out of baseband. In this pape...
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Using oversampled sigma-delta (/spl Sigma/-/spl Delta/) techniques a signal can be represented as a single bit binary data stream ({-1, 1}), with the quantization noise high pass filtered out of baseband. In this paper adaptive LMS digital filters are presented that directly use binary /spl Sigma/-/spl Delta/ input streams and update the PCM adaptive filter weights at the oversampled rate to realize architectures that are very suitable for mixed analog/digital VLSI implementation. Using the /spl Sigma/-/spl Delta/ adaptive architecture PCM values are multiplied by single bits, and can therefore be easily performed by a simple multiplexor. Also using the /spl Sigma/-/spl Delta/ approach, the decimation and interpolation stages required for converting from /spl Sigma/-/spl Delta/ to PCM (and vice-versa) suitable for Nyquist DSP algorithms are circumvented. The paper describes the sigma delta adaptive LMS filter architecture and presents preliminary results for adaptive echo cancellation using adaptive sigma delta and standard PCM architectures.< >
The implementation of signal processing algorithms on a heterogeneous multiprocessor system is examined. The signalprocessing algorithm, represented as a directed signal flow graph, is mapped to the multiprocessor sy...
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The implementation of signal processing algorithms on a heterogeneous multiprocessor system is examined. The signalprocessing algorithm, represented as a directed signal flow graph, is mapped to the multiprocessor system for execution. A heuristic scheme aimed at producing a schedule of minimum execution time is proposed. Communication overhead is incorporated in the scheduling. Simulation results are presented using both the proposed heuristic scheme and an optimum scheme based on the branch-and-bound approach. The heuristic results fall within a reasonable range from the optimal schedule.< >
Modern microprocessor technology is migrating from simply increasing clock speeds on a single processor to placing multiple processors on a die to increase throughput and power performance in every generation. To util...
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Modern microprocessor technology is migrating from simply increasing clock speeds on a single processor to placing multiple processors on a die to increase throughput and power performance in every generation. To utilize the potential of such a system, signal processing algorithms have to be efficiently parallelized so that the load can be distributed evenly among the multiple processing units. In this paper, we study several advanced deterministic and stochastic signal processing algorithms and their computation using multiple processing units. Specifically, we consider two commonly used time-frequency signal representations, the short-time Fourier transform and the Wigner distribution, and we demonstrate their parallelization with low communication overhead. We also consider sequential Monte Carlo estimation techniques such as particle filtering, and we demonstrate that its multiple processor implementation requires large data exchanges and thus a high communication overhead. We propose a modified mapping scheme that reduces this overhead at the expense of a slight loss in accuracy, and we evaluate the performance of the scheme for a state estimation problem with respect to accuracy and scalability.
The article addresses methods of adaptive signalprocessing in transmitting antenna arrays to enhance the interference resilience of digital radio links. It examines the usage of heuristic optimization algorithms for ...
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ISBN:
(数字)9798350373448
ISBN:
(纸本)9798350373455
The article addresses methods of adaptive signalprocessing in transmitting antenna arrays to enhance the interference resilience of digital radio links. It examines the usage of heuristic optimization algorithms for forming antenna array patterns considering the directions of signal and interference arrivals. The article presents algorithms of the matrix method for direct calculation of the required antenna pattern and optimization methods based on particle swarm optimization and salp swarm algorithms. To assess the effectiveness of the algorithms, simulations were conducted using a seven-element antenna array as an example. The research results demonstrate the potential for effectively adapting antenna array patterns to various interference conditions. Further research aims to conduct a comparative analysis of algorithm efficiency to determine the most energy-efficient method.
The authors introduce novel digital signal processing algorithms which can be used to measure various power system indicators, which, in turn, may be utilized for power quality assessment. They first discuss the signa...
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The authors introduce novel digital signal processing algorithms which can be used to measure various power system indicators, which, in turn, may be utilized for power quality assessment. They first discuss the signal analysis problem by providing classification of the assumptions about signal characteristics. Specific characteristics are a consequence of different power system disturbances. Two different classes of digital signal processing algorithms are introduced. These algorithms can be used for measurement of various quantities which may be used to characterize given disturbances. An approach to power quality assessment based on various measurements is illustrated by some examples.< >
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