In this paper we consider using 'digit serial' processing to build high performance parallel structures, in particular, parallel signal processors. Digit serial arithmetic processors have digit serial data tra...
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ISBN:
(纸本)0819406945
In this paper we consider using 'digit serial' processing to build high performance parallel structures, in particular, parallel signal processors. Digit serial arithmetic processors have digit serial data transmission combined with digit serial computation. Three digit serial arithmetic processors are presented and compared with their digit parallel counterparts. We show that by using a digit serial approach we can achieve a higher throughput than with a digit parallel processor, even though the two processors are structurally similar and have components of similar complexity.
The need to construct architectures in VLSI has focused attention on unnormalized floating point arithmetic. Certain unnormalized arithmetics allow one to 'pipe on digits,' thus producing significant speed up ...
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ISBN:
(纸本)0819406945
The need to construct architectures in VLSI has focused attention on unnormalized floating point arithmetic. Certain unnormalized arithmetics allow one to 'pipe on digits,' thus producing significant speed up in computation and making the input problems of special purpose devices such as systolic arrays easier to solve. We consider the error analysis implications of using unnormalized arithmetic in numerical algorithms. We also give specifications for its implementation. Our discussion centers on the example of Gaussian elimination. We show that the use of unnormalized arithmetic requires change in the analysis of this algorithm. We will show that only for certain classes of matrices that include diagonally dominant matrices (either row or column), Gaussian elimination is as stable in unnormalized arithmetic as in normalized arithmetic. However, if the diagonal elements of the upper triangular matrix are post normalized, then Gaussian elimination is as stable in unnormalized arithmetic as in normalized arithmetic for all matrices.
Inverse synthetic aperture radar (ISAR) is a radar imaging method by which the rotation of a target is utilized to produce a two dimensional image. To achieve high resolution in both range and cross range, a series of...
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ISBN:
(纸本)0819406945
Inverse synthetic aperture radar (ISAR) is a radar imaging method by which the rotation of a target is utilized to produce a two dimensional image. To achieve high resolution in both range and cross range, a series of stepped frequency waveforms are transmitted. These sample the target's radar response in frequency and time. Frequency transforms to time, which is proportional to range, and time transforms to doppler frequency, which is proportional to cross range. Therefore a two dimensional Fourier transform can be applied to the two dimensional data set to produce a radar image. However this is an approximation as the data is in a polar format, which only approximates a rectangular grid. Therefore resampling (interpolation) is required to change the grid from a polar to a rectangular format. The resampling in this case is straightforward. In an attempt to obtain higher resolution images, the Fourier transform has been replaced by the multiple signal classification (MUSIC) algorithm. The justification for this is that the targets of interest are manmade and so have sharp edges and corners. Therefore they consist of a number of corner reflectors with a background of continuous reflectors. The corner reflectors by their nature will generally give much stronger reflections, so one can with a certain degree of accuracy, approximate the ship as a collection of corner reflectors. Over the small change in aspect angle for which ISAR imaging is performed, corner reflectors can be approximated as point scatterers. This leads to the data being modeled as a collection of complex exponentials with added white Gaussian noise. The noise being due to thermal noise in the radar system. This type of data set is ideal for the two dimensional MUSIC algorithm. There are two major difficulties in applying the MUSIC algorithm to ISAR imaging. First, the MUSIC estimator is more sensitive to the sampling grid being polar than the Fourier transform is. Second, the resampling is less effect
An efficient algorithm is presented for computing the continuous wavelet transform and the wideband ambiguity function on a sample grid with uniform time spacing but arbitrary sampling in scale. The method is based on...
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ISBN:
(纸本)0819406945
An efficient algorithm is presented for computing the continuous wavelet transform and the wideband ambiguity function on a sample grid with uniform time spacing but arbitrary sampling in scale. The method is based on the chirp z-transform and requires the same order of computation as constant-bandwidth analysis techniques, such as the short-time Fourier transform and the narrowband ambiguity function. An alternative spline approximation method which is more efficient when the number of scale samples is large is also described.
A general approach for obtaining joint representations in signal analysis is presented. The method is applied to scale representations. We define a new scale operator and show that it leads to joint representations of...
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ISBN:
(纸本)0819406945
A general approach for obtaining joint representations in signal analysis is presented. The method is applied to scale representations. We define a new scale operator and show that it leads to joint representations of the Altes and Marinovic type and we also define joint representations with inverse frequency and show that it leads to Bertrand-Bertrand type distributions. We derive the uncertainty principle for scale and obtain the minimum time-scale uncertainty signal.
We compare the modified Wigner distribution functions obtained via the Choi-Williams kernel and its rotation, as well as by the tilted Gaussian kernel. Based on several commonly used examples, we demonstrate that the ...
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ISBN:
(纸本)0819406945
We compare the modified Wigner distribution functions obtained via the Choi-Williams kernel and its rotation, as well as by the tilted Gaussian kernel. Based on several commonly used examples, we demonstrate that the modified Wigner distribution obtained via the Gaussian kernel can minimize the artifacts more effectively and has the capability of selectively filtering out undesired components.
A high performance VLSI architecture to perform combined multiply-accumulate, divide, and square root operations is proposed. The circuit is highly regular, requires only minimal control, and can be pipelined right do...
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ISBN:
(纸本)0819406945
A high performance VLSI architecture to perform combined multiply-accumulate, divide, and square root operations is proposed. The circuit is highly regular, requires only minimal control, and can be pipelined right down to the bit level. The system can also be reconfigured on every cycle to perform one or more of these operations. The throughput rate for each operation is the same and is wordlength independent. This is achieved using redundant arithmetic. With current CMOS technology, throughput rates in excess of 80 million operations per second are expected.
In many applications (radar, communication, plasma physics) the signal of interest is sinusoidal and is hidden in non-white noise. The multi-window method of spectrum estimation gives a constant false alarm test for t...
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ISBN:
(纸本)0819406945
In many applications (radar, communication, plasma physics) the signal of interest is sinusoidal and is hidden in non-white noise. The multi-window method of spectrum estimation gives a constant false alarm test for the presence of a sinusoid in a time series if the noise can be assumed Gaussian. In this paper we generalize the method to an array and study the resulting test. Expressions for the probabilities of detection and of false alarm are obtained analytically and receiver operation characteristic curves are computed for a particular scenario under different conditions.
We present an analysis and computational results relating to the regularized restoration of subpixel information from undersampled data. The method makes use of a small set of images in various stages of defocus. An i...
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ISBN:
(纸本)0819406945
We present an analysis and computational results relating to the regularized restoration of subpixel information from undersampled data. The method makes use of a small set of images in various stages of defocus. An iterative implementation permits the incorporation of a non- negativity constraint. The problem we consider is fundamentally under-determined, but useful results can be obtained in reasonably low noise conditions.
The well-known uncertainty principle is often invoked in signalprocessing. It is also often considered to have the same implications in signal analysis as does the uncertainty principle in quantum mechanics. The unce...
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ISBN:
(纸本)0819406945
The well-known uncertainty principle is often invoked in signalprocessing. It is also often considered to have the same implications in signal analysis as does the uncertainty principle in quantum mechanics. The uncertainty principle is often incorrectly interpreted to mean that one cannot locate the time-frequency coordinates of a signal with arbitrarily good precision, since, in quantum mechanics, one cannot determine the position and momentum of a particle with arbitrarily good precision. Renyi information of the third order is used to provide an information measure on time-frequency distributions. The results suggest that even though this new measure tracks time-bandwidth results for two Gabor log-ons separated in time and/or frequency, the information measure is more general and provides a quantitative assessment of the number of resolvable components in a time frequency representation. As such, the information measure may be useful as a tool in the design and evaluation of time-frequency distributions.
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