We present here some algorithms for on-line computation of elementary functions. These algorithms use shift-and-add as elementary step and need signed digit representations of numbers. Then, we give some theoretical r...
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ISBN:
(纸本)0819406945
We present here some algorithms for on-line computation of elementary functions. These algorithms use shift-and-add as elementary step and need signed digit representations of numbers. Then, we give some theoretical results about on-line computation of functions. For instance, we show that a finite automaton (in practice a bounded size and memory operator) can compute in on-line only piecewise affine functions.
An algorithm is proposed to compute samples of any bilinear joint time-frequency representation of the Cohen's class. The computation is performed on a decimated sampling grid, mapping N = 3BD signal samples into ...
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ISBN:
(纸本)0819416207
An algorithm is proposed to compute samples of any bilinear joint time-frequency representation of the Cohen's class. The computation is performed on a decimated sampling grid, mapping N = 3BD signal samples into N = K × L critical samples of the joint representation in the time-frequency domain. This is in contrast with the usual approaches that perform the computation on a much denser grid, mapping N signal samples into N × N samples in the time-frequency plane. The algorithm is based on the discrete Zak transform and represents an extension of the work by Auslander et al. on fast computation of the ambiguity function. For a number of popular representations, the algorithm is shown to have computational complexity about the same as an ordinary FFT.
Several Elliptic Curve Processors (ECP) have been proposed in the literature associated with various architectures using different and sometimes confusing terminologies. This paper is a short review study of ECP archi...
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ISBN:
(纸本)9781467377881
Several Elliptic Curve Processors (ECP) have been proposed in the literature associated with various architectures using different and sometimes confusing terminologies. This paper is a short review study of ECP architectures, considering the hardware platforms used for their implementations. The main design parameters of the ECP architectures, including the field choice and scalar multiplication algorithms were identified. Based on these parameters, a statistical study is conducted on a large collection of the published work. From the analysis of the collected data, several conclusions were deduced, such as the notion that binary field is easier to be implemented in hardware than prime field as well as the polynomial basis is dominant over other bases representation. Another significant conclusion is that Montgomery scalar multiplier has been used more than Lopez-Dahab, Binary, and NAF methods, particularly with the dominance of Lopez-dahab Projective coordinate.
This paper presents an overview of adaptive nonlinear filters equipped with bilinear system models. Bilinear filters are recursive nonlinear systems that belong to the class of polynomial systems. Because of the feedb...
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ISBN:
(纸本)0819416207
This paper presents an overview of adaptive nonlinear filters equipped with bilinear system models. Bilinear filters are recursive nonlinear systems that belong to the class of polynomial systems. Because of the feedback structure, such models are able to represent many nonlinear systems efficiently. The paper first describe stochastic gradient adaptive bilinear filters. The class of recursive least-squares adaptive bilinear filters are discussed next. Stability issues associated with bilinear system models and adaptive bilinear filters are also discussed in the paper. The paper concludes with an experimental comparison of the performance of linear, truncated second-order volterra, and bilinear system models in a nonlinear channel equalization problem.
In this paper, we show how quadratic time-frequency representations are a generalization of the spectrogram and we review our results for time-frequency analysis and display of chirps and speech. We then show comparat...
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ISBN:
(纸本)0819406945
In this paper, we show how quadratic time-frequency representations are a generalization of the spectrogram and we review our results for time-frequency analysis and display of chirps and speech. We then show comparative performance on phase-shifted keyed communication signals. The concept of quadratic filtering is then introduced and linked to Teager's energy detector and the resolution advantages over linear filtering are demonstrated.
The Wigner Distribution Function (WDF) is a time-frequency descriptor capable of tracking the time-varying second order statistics in a signal. In this paper, we characterize linear systems in terms of the WDFs of the...
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Sensor network technology can revolutionize the study of animal ecology by providing a means of non-intrusive, simultaneous monitoring of interaction among multiple animals. In this paper, we investigate design, analy...
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Sensor network technology can revolutionize the study of animal ecology by providing a means of non-intrusive, simultaneous monitoring of interaction among multiple animals. In this paper, we investigate design, analysis, and testing of acoustic arrays for localizing acorn woodpeckers using their vocalizations.1,2 Each acoustic array consists of four microphones arranged in a square. All four audio channels within the same acoustic array are finely synchronized within a few micro seconds. We apply the approximate maximum likelihood (AML) method3 to synchronized audio channels of each acoustic array for estimating the direction-of-arrival (DOA) of woodpecker vocalizations. The woodpecker location is estimated by applying least square (LS) methods to DOA bearing crossings of multiple acoustic arrays. We have revealed the critical relation between microphone spacing of acoustic arrays and robustness of beamforming of woodpecker vocalizations. Woodpecker localization experiments using robust array element spacing in different types of environments are conducted and compared. Practical issues about calibration of acoustic array orientation are also discussed.
A streak camera is a recording instrument in which spatial image is swept in time. creating a spatial-temporal image on a charge-coupled device (CCD). Traditional analysis for captured image data has been using unifor...
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ISBN:
(纸本)0819454974
A streak camera is a recording instrument in which spatial image is swept in time. creating a spatial-temporal image on a charge-coupled device (CCD). Traditional analysis for captured image data has been using uniform and as sampling points, in which a block of CCD pixel readouts are summed to give one reading. Equivalently simple area moving averages are applied concurrently while sampling, and high frequency content is reduced. To solve this problem. we use peak-value sampling procedure, based on the view from photoelectron statistics. After background correction. maximum values in spatial dimensions are selected to obtain time series data. A DSP filter is then applied and optimized for this time series. A Welch algorithm fast Fourier transform is applied to obtain power spectra. Segmented cumulative spectra is then calculated for global statistics and related to time domain fluctuations. Self similarity at different sweeping time-scales is used to recognize CCD pattern noise. Sinusoidal pattern noise is automatically corrected by peak-value sampling. Computational results show that time-frequency analysis using peak-value sampling algorithm and similar variants is far more effective in discovering high frequency oscillatory noise than traditional uniform binned sampling. We have applied this algorithm to analyze data produced by a 4096x4096 CCD streak camera illuminated with a macro pulse laser. High frequency oscillations in 6similar to10 GHz region were found in laser spectra. Spatial-temporal oscillations of this range are difficult to diagnose with conventional optoelectronic detectors on a per-shot basis. This work has led to improvement of laser design.
Compressive Sensing (CS) is a novel scheme, in which a signal that is sparse in a known transform domain can be reconstructed using fewer samples. The signal reconstruction techniques are computationally intensive and...
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ISBN:
(纸本)9781628410464
Compressive Sensing (CS) is a novel scheme, in which a signal that is sparse in a known transform domain can be reconstructed using fewer samples. The signal reconstruction techniques are computationally intensive and have sluggish performance, which make them impractical for real-time processing applications. The paper presents novel architectures for Orthogonal Matching Pursuit algorithm, one of the popular CS reconstruction algorithms. We show the implementation results of proposed architectures on FPGA, ASIC and on a custom many-core platform. For FPGA and ASIC implementation, a novel thresholding method is used to reduce the processing time for the optimization problem by at least 25%. Whereas, for the custom many-core platform, efficient parallelization techniques are applied, to reconstruct signals with variant signal lengths of N and sparsity of m. The algorithm is divided into three kernels. Each kernel is parallelized to reduce execution time, whereas efficient reuse of the matrix operators allows us to reduce area. Matrix operations are efficiently paralellized by taking advantage of blocked algorithms. For demonstration purpose, all architectures reconstruct a 256-length signal with maximum sparsity of 8 using 64 measurements. Implementation on Xilinx virtex-5 FPGA, requires 27.14 mu s to reconstruct the signal using basic OMP. Whereas, with thresholding method it requires 18 mu s. ASIC implementation reconstructs the signal in 13 mu s. However, our custom many-core, operating at 1.18 GHz, takes 18.28 mu s to complete. Our results show that compared to the previous published work of the same algorithm and matrix size, proposed architectures for FPGA and ASIC implementations perform 1.3x and 1.8x respectively faster. Also, the proposed many-core implementation performs 3000x faster than the CPU and 2000x faster than the GPU.
The proceedings include 28 papers, 27 of them are indexed separately. Topics covered include advanced techniques of real-time signalprocessing in various fields, such as space information systems, radar data processi...
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The proceedings include 28 papers, 27 of them are indexed separately. Topics covered include advanced techniques of real-time signalprocessing in various fields, such as space information systems, radar data processing, missile guidance underwater acoustic imaging, wideband integrated optics. Also hardware architectures and algorithms for real-time signalprocessing are considered. Several presentations are devoted to digital approaches and analog implementations of real-time signalprocessing.
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