We present an efficient optimal algorithm that allocates and schedules cyclic synchronous tasks into fully connected processors. We consider applications with cyclic synchronous tasks with heavy communication traffic,...
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We present an efficient optimal algorithm that allocates and schedules cyclic synchronous tasks into fully connected processors. We consider applications with cyclic synchronous tasks with heavy communication traffic, which run on multiprocessors with a fully connected communication network. We suggest the computing period as the performance measure to minimize the overall computation time. We use an individual start policy for task scheduling, and also introduce concepts and characteristics of the local period and the global period. To solve the complicated optimal scheduling problem in an efficient way, we propose a new spatial scheduling technique using scheduling space which represents all possible schedules in multi-dimensional space. By using spatial searching and an enhanced branch-and-bound technique, the optimal task allocation and schedule which minimizes the computing period can be found efficiently. Various examples and scheduling results show the efficiency of the proposed algorithm.
This paper presents a new algorithm on lower-power survivor path memory implementation of the trace-back systolic array Viterbi algorithm. A novel idea is to reuse the already-generated trace-back routes to reduce the...
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This paper presents a new algorithm on lower-power survivor path memory implementation of the trace-back systolic array Viterbi algorithm. A novel idea is to reuse the already-generated trace-back routes to reduce the number of trace-back operations. It results in increasing the area of spurious switching activity region, and further reducing the switching activity with gated-clocks during trace-back operation. With the SYNOPSYS power estimation tool, DesignPower, our experimental result shows on the average 40% reduction in power with the same latency at a cost of 23% increase in area against the trace-back unit introduced by Truong et al. (1992). The proposed survivor memory scheme can be applied to the digital communication systems for targeting low power consumption.
The proceedings contains 58 papers from the conference of SPIE: advancedsignalprocessingalgorithms, Architectures, and Implementations VIII. The topics discussed include: blind channel identification and extraction...
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The proceedings contains 58 papers from the conference of SPIE: advancedsignalprocessingalgorithms, Architectures, and Implementations VIII. The topics discussed include: blind channel identification and extraction of more sources than sensors;blind channel estimation for CDMA systems with orthogonal modulation;blind equalization and source separation with MSK inputs and adaptive blind channel estimation by least-squares smoothing for CDMA.
We generalize the concept of the autocorrelation function to arbitrary physical variables and show how it can be used to define a local autocorrelation function. Using the local autocorrelation function we develop a n...
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ISBN:
(纸本)0819429163
We generalize the concept of the autocorrelation function to arbitrary physical variables and show how it can be used to define a local autocorrelation function. Using the local autocorrelation function we develop a new method to generate densities for arbitrary physical quantities. In addition, we show that the generalized autocorrelation function can be used to characterize functions with respect to a physical property.
This paper presents an application of formal mathematics to create a high performance, low power architecture for time-frequency and time-scale computations implemented in asynchronous circuit technology that achieves...
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ISBN:
(纸本)0819429163
This paper presents an application of formal mathematics to create a high performance, low power architecture for time-frequency and time-scale computations implemented in asynchronous circuit technology that achieves significant power reductions and performance enhancements over more traditional approaches. Utilizing a combination of concepts from multirate signalprocessing and asynchronous circuit design, a case study is presented dealing with a new architecture for the fast Fourier transform, an algorithm that requires globally shared results. Then, the generalized distributive law is presented as an important paradigm for advanced asynchronous hardware design.
Searching for wideband short duration chirps is an important issue in spectrum surveillance. We propose a method and apparatus, inspired by optical tomography, by which a one-dimensional signal is converted to a two-d...
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ISBN:
(纸本)0819429163
Searching for wideband short duration chirps is an important issue in spectrum surveillance. We propose a method and apparatus, inspired by optical tomography, by which a one-dimensional signal is converted to a two-dimensional image. This image has the remarkable property that it may disclose discernible structure. A chirp in additive white Gaussian noise, even undersampled, may be detected. The process is inherently linear and may be easily implemented by parallel processing or through the construction of an optoelectronic device.
An innovative approach is being used to implement and simulate the infrared (IR) and laser radar signalprocessingalgorithms for the advanced Sensor Technology Program (ASTP) and the Discrimination Interceptor Techno...
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ISBN:
(纸本)0819428221
An innovative approach is being used to implement and simulate the infrared (IR) and laser radar signalprocessingalgorithms for the advanced Sensor Technology Program (ASTP) and the Discrimination Interceptor Technology Program (DITP). Although the algorithms will run on four different computer architectures, they will use the same source code for all implementations. The initial development and testing will occur in Mathcad on a Windows 95/NT personal computer, then move to simulation on a Silicon Graphics (SGI) workstation, then to scaled real-time simulation on a parallel high performance computer (HPC), and finally to the actual flight processor, the miniaturized parallel Wafer Scale signal Processor (WSSP) with a MIMD (multiple-instruction and multiple data) architecture. This flexibility is accomplished with code wrappers that implement interchangeable interface layers for the code modules, one wrapper for Mathcad matrices, one for C++ objects on the workstation, one for message passing with static routing on the HPC, and one for dynamically routed message passing on the WSSP. With this approach, developers can move modules back and forth from the workstation simulation environment to the implementation hardware. This will eliminate the need to maintain different versions of the same algorithm. The signalprocessingalgorithms will be modified to work in a massively parallel architecture, with a message passing interface, which is simulated on the Silicon Graphics workstation, emulated on the HPC, and implemented on the WSSP. This approach will allow for pipeline processing as well as multiple, concurrently running instances of modules. In addition, innovative algorithms will fuse active laser radar detections and passive multicolor IR sensor measurements to improve target state estimation.
Computationally efficient algorithms which perform speech activity detection have significant potential economic and labor saving benefit, by automating an extremely tedious manual process. In many applications, it is...
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ISBN:
(纸本)0819429163
Computationally efficient algorithms which perform speech activity detection have significant potential economic and labor saving benefit, by automating an extremely tedious manual process. In many applications, it is desirable to extract intervals of speech which are bounded by segments of other signal types (fax/modem, music, static, dial tones, etc.). In the past, algorithms which successfully discriminate between speech and one specific other signal type have been developed. Frequently, these algorithms fail when the specific non-speech signal is replaced by a different non-speech signal. Little work has been done on combining such discriminators in order to solve the general speech vs. non-speech discrimination problem. Typically, several signal specific discriminators are blindly combined with predictable negative results. Moreover, when a large number of discriminators are involved, dimension reduction is achieved using Principal Components, which optimally compresses signal variance into the fewest number of dimensions. Unfortunately, these new coordinates are not necessarily optimal for discrimination. In this paper we apply graphical tools to determine a set of discriminators which produce excellent speech vs. non-speech clustering, thereby eliminating the guesswork in selecting good feature vectors. This cluster structure provides a basis for a general multivariate speech vs. non-speech discriminator, which compares very favorably with the TALKATIVE speech extraction algorithm.
A deconvolution technique to estimate the Evolutionary Spectrum (ES) of nonstationary signals by deconvolving the blurring effects of the kernel function fi om bilinear time frequency distributions (TFD) is presented....
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ISBN:
(纸本)0819429163
A deconvolution technique to estimate the Evolutionary Spectrum (ES) of nonstationary signals by deconvolving the blurring effects of the kernel function fi om bilinear time frequency distributions (TFD) is presented. The resulting ES has desirable properties such as positivity, higher resolution, higher concentration in time-frequency. The proposed algorithm is computationally more efficient compared to the recently proposed entropy based deconvolution method. Unlike the entropy method the new algorithm can be adapted to deconvolve TFDs other than the spectrogram.
In this report, we propose combining the Total Variation denoising method with the high loss wavelet compression for high noise level images. Numerical experiments show that TV-denoising can bring more wavelet coeffic...
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ISBN:
(纸本)0819429163
In this report, we propose combining the Total Variation denoising method with the high loss wavelet compression for high noise level images. Numerical experiments show that TV-denoising can bring more wavelet coefficients closer to zero thereby making the compression more efficient while the salient features (edges) of the images can still be retained.
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