This paper presents a complete methodology for the automatic synthesis of VLSI architectures used in digital signalprocessing. Most signal processing algorithms have the form of an n-dimensional nested loop with unit...
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This paper presents a complete methodology for the automatic synthesis of VLSI architectures used in digital signalprocessing. Most signal processing algorithms have the form of an n-dimensional nested loop with unit uniform loop carried dependencies. We model such algorithms with generalized UET grids. We calculate the optimal makespan for the generalized UET grids and then we establish the minimum number of systolic cells required for achieving the optimal makespan. We present a complete methodology for the hardware synthesis of the resulting architecture, based on VHDL. This methodology automatically detects all necessary computation and communication elements and produces optimal layouts. The complexity of our proposed scheduling policy is completely independent of the size of the nested loop and depends only on its dimension, thus being the most efficient (in terms of complexity) known to us. All these methods were implemented and incorporated in an integrated software package which provides the designer with a powerful parallel design environment, from high level signalprocessing algorithmic specifications to low-level (i.e., actual layouts) optimal implementation. The evaluation was performed using well-known algorithms from signalprocessing.
Field Programmable Gate Array (FPGA) architectures have emerged as an alternative means of implementing complex logic circuits providing rapid manufacturing turnaround time and low prototyping costs. This paper presen...
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Field Programmable Gate Array (FPGA) architectures have emerged as an alternative means of implementing complex logic circuits providing rapid manufacturing turnaround time and low prototyping costs. This paper presents a new FPGA architecture suitable for the application specific signal processing algorithms and Wafer-Scale integration (WSI) Technology. The architecture must be designed for versatility, flexibility, high speed, improved logic density, and defect tolerance. The proposed FPGA architecture consists of 2 dimensional array of programmable logic elements based on look-up table, interconnection resources, and input/output (I/O) blocks. The architectural style is similar to the one used in XILINX FPGA architecture. A key variation from the commonly used FPGA is the dual switching scheme employed in the proposed architecture. The design methodology, the design tools, and results obtained by using a Segmented Channel Routing algorithm to map on it a 16 bit parallel multiplier, are presented.
A new approach for parallelism analysis and extraction of digital signal processing algorithms is introduced. The high level description of the input is given in CIRCAL. A dependency graph of the problem is constructe...
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A new approach for parallelism analysis and extraction of digital signal processing algorithms is introduced. The high level description of the input is given in CIRCAL. A dependency graph of the problem is constructed to check existence of cycles. Loops in the dependency graph are parallelized. The approach is illustrated by an example.< >
In this paper, we explore the use of multi-stage adaptation algorithms for a variety of adaptive filtering applications where the structure of the underlying process to be estimated is unknown. These algorithms are &q...
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In this paper, we explore the use of multi-stage adaptation algorithms for a variety of adaptive filtering applications where the structure of the underlying process to be estimated is unknown. These algorithms are "multi-stage" in that they comprise multiple adaptive filtering algorithms that operate in parallel on the observation sequence, and adaptively combine the outputs of this first stage to form an overall signal estimate. Several examples of this class of algorithms are demonstrated and analyzed in both a deterministic and stochastic context with respect to their convergence and mean squared error. The first example of this class, a "universal" linear predictor, was recently introduced and shown to asymptotically achieve the performance of the best linear predictor for each sequence, (up to some maximal order). Two new algorithms have been developed that generalize this universal linear predictor, and explore the use of the LMS algorithm in each stage of adaptation. Each of these algorithms are compared through theoretical analysis of their behavior.
algorithms for real-time parallel processing of an audio signal in large-scale digital audio distribution networks, implemented on personal computer platform, are compared in this paper from the performance point of v...
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ISBN:
(纸本)9781424460830
algorithms for real-time parallel processing of an audio signal in large-scale digital audio distribution networks, implemented on personal computer platform, are compared in this paper from the performance point of view. In such systems, the summing and multiplication of audio signal take up a significant portion of the processing power of the system. Therefore, there is a tendency to decrease its computing demands and thus reserve the computing power of the processor for other signalprocessing modules in the audio network. Various approaches can therefore be used to distribute computing among several threads. Seven approaches are analyzed in the paper and fastest one is found with regard to the size of audio sample buffers.
Non-contacting methods for strain and displacement measurement are now well established, although not in very wide spread use in material science applications. Besides other methods, laser speckle pattern shift techni...
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Non-contacting methods for strain and displacement measurement are now well established, although not in very wide spread use in material science applications. Besides other methods, laser speckle pattern shift techniques can be successfully used for strain and displacement measurements. Using such a technique, one is confronted with the problem of calculating speckle pattern shift values from a time series of images. In this paper, we present a new set of algorithms based on minimum-mean-square error and maximum likelihood principles suitable for this task. We show their application in two different strain and displacement measurement set-ups.
This paper reviews the mathematical basis for two popular algorithms - the Kalman filter used in control and the adaptive FIR filter used in signalprocessing. These estimation algorithms are compared and discussed. T...
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This paper reviews the mathematical basis for two popular algorithms - the Kalman filter used in control and the adaptive FIR filter used in signalprocessing. These estimation algorithms are compared and discussed. They are reformulated into the generalized frequency domain to yield alternative algorithms such as Walsh, Haar, and slant.
Implementing signal-processingalgorithms on multiple programmable signal processors has the potential for providing increased throughput. The capability can be utilized for implementing more complex code, extending t...
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Implementing signal-processingalgorithms on multiple programmable signal processors has the potential for providing increased throughput. The capability can be utilized for implementing more complex code, extending the frequency range of application of programmable signal processors, or substituting less costly processors for expensive fast processors. Results obtained in applying heuristic algorithms to the scheduling of code of seven practical applications in signal and image processing are reported.< >
Functional magnetic resonance imaging (fMRI) investigations are increasingly important for the in vivo study and modeling of integrative brain functions in health and disease, where sophisticated mathematical and stat...
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Functional magnetic resonance imaging (fMRI) investigations are increasingly important for the in vivo study and modeling of integrative brain functions in health and disease, where sophisticated mathematical and statistical algorithms for fMRI signalprocessing and interpretation have come into play. Apart from neuroanatomical, neurophysiological, and neuropsychological competence, the progress in cognitive neuroscience and brain mapping is critically dependent on expertise from other disciplines - such as statistics, computer science, and electrical and electronic engineering dealing with signalprocessing, circuits and systems. During the last years, there has also been a trend towards funding of "open science" consortia, providing huge and well-curated image data repositories together with advanced software tools and processing pipelines to be used and further developed by the research community.
It is shown that a large set of (non necessarily stationary) correlation matrices may be transformed into a matrix that consists of essentially banded subblocks. The transformation is accompanied by pre- and postmulti...
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It is shown that a large set of (non necessarily stationary) correlation matrices may be transformed into a matrix that consists of essentially banded subblocks. The transformation is accompanied by pre- and postmultiplication with an orthogonal matrix whose elements are derived from the impulse responses of a suitably designed cascade of alias free multirate analysis filter banks. It is further proved that the Cholesky factor of the transformed matrix also consists of essentially banded subblocks. These two observations are combined to show that the linear positive definite systems of equations that arise in statistical signalprocessing can be solved in O(max(N log /sup 2/(N), N/sup 2/)) operations while matrix-vector multiplication steps may be implemented in O(n log (N)) operations. An error analysis of the proposed linear positive definite system solver is also provided.< >
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