We present a high performance implementation of the FFT algorithm on the BOPS ManArray parallel DSP processor. The ManArray we consider for this application consists of an array controller and 2 to 4 fully interconnec...
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We present a high performance implementation of the FFT algorithm on the BOPS ManArray parallel DSP processor. The ManArray we consider for this application consists of an array controller and 2 to 4 fully interconnected processing elements. To expose the parallelism inherent to an FFT algorithm we use a factorization of the DFT matrix in Kronecker products, permutation and diagonal matrices. Our implementation utilizes the multiple levels of parallelism that are available on the ManArray. We use the special multiply complex instruction, that calculates the product of two complex 32-bit fixed point numbers in 2 cycles (pipelinable). Instruction level parallelism is exploited via the indirect Very Long Instruction Word (iVLIW). With an iVLIW, in the same cycle a complex number is read from memory, another complex number is written to memory, a complex multiplication starts and another finishes, two complex additions or subtractions are done and a complex number is exchanged with another processing element. Multiple local FFTs are executed in Single Instruction Multiple Data (SIMD) mode, and to avoid a costly data transposition we execute distributed FFTs in Synchronous Multiple Instructions Multiple Data (SMIMD) mode.
The proceedings contains 58 papers from the conference of SPIE: advanced signal processing algorithms, 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: advanced signal processing algorithms, 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.
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 conventional resolution of individual emitters or frequencies within a cluster is limited by the physical dimensions and electrical aspects (such as the bandwidth) of a sensor system. Super-resolution describes al...
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The conventional resolution of individual emitters or frequencies within a cluster is limited by the physical dimensions and electrical aspects (such as the bandwidth) of a sensor system. Super-resolution describes algorithmic techniques that potentially enhance the conventional degree of resolution. Although there has been considerable research into super-resolution techniques (since 1970), there has, in contrast, been very little that addresses the fundamental bound of resolution performance that should theoretically be achievable by a 'perfect' algorithm in ideal conditions. The purpose of this paper is to present a generic method for predicting the fundamental resolution limit. We show that the resolution of closely-spaced signal waveforms is intrinsically linked to the signal-to-noise ratios of those signals. The method can be applied to individual spatial, temporal or spectral discriminants or to multi-discriminant systems. Loss of SNR resulting from the need to separate signals is derived both for the matched filter case and for eigen decomposition.
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.
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.
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.
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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