Linear Algebra (i. e. , the algebra of vector spaces) provides widely used mathematical tools and concepts which are today considered for implementation in special computer architectures. It seems that so many signal ...
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ISBN:
(纸本)0892524669
Linear Algebra (i. e. , the algebra of vector spaces) provides widely used mathematical tools and concepts which are today considered for implementation in special computer architectures. It seems that so many signalprocessing problems can be expressed and, more importantly, implemented efficiently as a sequence of vector and matrix operations, that a signalprocessing system with a capability for high speed linear algebra is necessary if the more advancedsignalprocessingalgorithms are to be implemented to operate in real time. This paper supports the notion that linear algebra is a sound basis for important signalprocessing system implementations and suggests that multilinear algebra (i. e. , the algebra of vector, bivector, trivector, etc. spaces) offers an even broader set of signalprocessing tools. Examples and ideas from direction finding and time series analysis are discussed.
Focussing techniques have proven efficient in direction-of-arrival estimation of broadband signals. However, when used alone at high frequency operation, these techniques cannot accurately locate the sources, due to t...
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Focussing techniques have proven efficient in direction-of-arrival estimation of broadband signals. However, when used alone at high frequency operation, these techniques cannot accurately locate the sources, due to the numerous spurious peaks in the spectrum. Since the spurious peaks depend on the array manifold, their location varies from one focussing frequency to another. Improved jammer localization can, therefore, be achieved by focussing at different frequencies and then averaging the corresponding MUSIC spectra. The averaging smooths out the undesired peaks while boosting the common spectral peaks, allowing correct detection and location of the waveforms impinging on the array.
We introduce the use of multidimensional logarithmic number system (MDLNS) as a generalization of the classical 1-D logarithmic number system (LNS) and analyze its use in DSP applications. The major drawback of the LN...
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We introduce the use of multidimensional logarithmic number system (MDLNS) as a generalization of the classical 1-D logarithmic number system (LNS) and analyze its use in DSP applications. The major drawback of the LNS is the requirement to use very large ROM arrays in implementing the additions and subtraction and it limits its use to low-precision applications. MDLNS allows exponential reduction of the size of the ROMs used without affecting the speed of the computational process: moreover, the calculations over different bases and digits are completely independent, which makes this particular representation perfectly suitable for massively parallel DSP architectures. The use of more than one base has at least two extra advantages. Firstly, the proposed architecture allows us to obtain the final result straightforwardly in binary form, thus, there is no need of the exponential amplifier, used in the known LNS architectures. Secondly, the second base can be optimized in accordance to the specific digital filter characteristics. This leads to dramatic reduction of the exponents used and, consequently, to large area savings. We offer many examples showing the computational advantages of the proposed approach.
This paper describes a scheduling method for hard real-time Digital signalprocessing (DSP) applications, implemented on a multi-processor. Due to the very high operating frequencies of DSP applications (typically hun...
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ISBN:
(纸本)0819416207
This paper describes a scheduling method for hard real-time Digital signalprocessing (DSP) applications, implemented on a multi-processor. Due to the very high operating frequencies of DSP applications (typically hundreds of kHz) runtime overhead should be kept as small as possible. Because static scheduling introduces very little run-time overhead it is used as much as possible. Dynamic pre-emption of tasks is allowed if and only if it leads to better performance in spite of the extra run-time overhead. We essentially combine static scheduling with dynamic pre-emption using static priorities. Since we are dealing with hard real-time applications we must be able to guarantee at compile-time that all timing requirements will be satisfied at run-time. We will show that our method performs at least as good as any static scheduling method. It also reduces the total amount of dynamic pre-emptions compared with run time methods like deadline monotonic scheduling.
In this paper, we use the concept of evolutionary spectrum to solve key problems in array processing. We present Cross-power Evolutionary Periodogram for direction finding and blind separation of nonstationary signals...
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In this paper, we use the concept of evolutionary spectrum to solve key problems in array processing. We present Cross-power Evolutionary Periodogram for direction finding and blind separation of nonstationary signals. We model nonstationary signals received by each sensor in the array as a sum of complex sinusoids with time-varying amplitudes. These amplitudes carry information about the direction of arrival which may also be time-varying. We first estimate the time-varying amplitudes, then use the results for the estimation of evolutionary cross-power distributions of the sensor data. Next, using cross-power estimates at time-frequency samples of interest, we estimate the directions of arrival using one of the existing high resolution direction finding methods. If the directions are time-varying, we select time-frequency points around the time of interest. By carrying out the estimation at different times, we obtain the directions as a function of time. If the sources are stationary, then we can use all time-frequency points of interest for the estimation of fixed directions. We also use whitening and subspace methods to find the mixing matrix and separate the signals received by the array. Simulation examples illustrating the performances of the proposed algorithms are presented.
The research work reported in this paper is concerned with the use of higher order spectral estimation techniques as a means to deriving the parameters of 2D autoregressive (AR) models. Image analysis is examined from...
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ISBN:
(纸本)0819416207
The research work reported in this paper is concerned with the use of higher order spectral estimation techniques as a means to deriving the parameters of 2D autoregressive (AR) models. Image analysis is examined from a higher order statistical perspective and in the context of noise. The objective is to develop analysis techniques through which robust autoregressive parameter estimation is accomplished. The approach taken involves the use of 2D AR models derive from third order cumulants. The directionality of the cumulant space influences the AR parameter estimation in a decisive manner. The specific application of the developed methods is in mammography, an area in which it is very difficult to discern the appropriate features. The results show significant discriminating gains through such techniques.
We compare the performance of three parallel supercomputers executing a bispectrum estimation code used to remove distortions from astronomical data. We discuss the issues in parallelizing the code on an 8-processor s...
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ISBN:
(纸本)0819406945
We compare the performance of three parallel supercomputers executing a bispectrum estimation code used to remove distortions from astronomical data. We discuss the issues in parallelizing the code on an 8-processor shared-memory CRAY Y-MP and a 1024-processor distributed-memory nCUBE machine. Results show that elapsed times on the nCUBE machine are comparable to those on the CRAY Y-MP. Execution of the nCUBE was more than 40 times faster than that of a single processor CRAY-2 resulting in more than 50 times better cost performance. Cost performance on the nCUBE is more than 25 times better than an 8- processor CRAY Y-MP.
The scale dependent wavelet transform can be augmented by a rotation dependent version as well as other generalizations. Tomographic analysis and line segment transforms are special cases of rotation dependent wavelet...
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The scale dependent wavelet transform can be augmented by a rotation dependent version as well as other generalizations. Tomographic analysis and line segment transforms are special cases of rotation dependent wavelet analysis. Other cases suggested by biological analogy9 are a rotation dependent edge segment transform (using edge segments rather than line segments) and a binocular rotation dependent wavelet transform that introduces depth information into the reconstructed image. Applications to robot vision and synthetic aperture radar appear particularly promising.
We develop redundant CORDIC scheme where the scale factor is forced to be constant while computing angles for 2 × 1 plane rotations. Based on the scheme, we present a fixed-point implementation of matrix triangul...
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We develop redundant CORDIC scheme where the scale factor is forced to be constant while computing angles for 2 × 1 plane rotations. Based on the scheme, we present a fixed-point implementation of matrix triangularization by Luk's parallel algorithm, with the following additional features: (1) the final scaling operation is done by shifting, (2) the number of iterations in CORDIC rotation unit is reduced by about 25% by expressing the direction of the rotation in radix-2 and radix-4, and (3) the conventional number representation of rotated output is obtained on-the-fly, not from a carry-propagate adder. The number of hardware modules and the speed are evaluated and compared with the previous CORDIC schemes.
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