Amin et. al. recently developed a time-frequency MUSIC algorithm with narrow band models for the estimation of direction of arrival (DOA) when the source signals are chirps. In this research, we consider wideband mode...
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Amin et. al. recently developed a time-frequency MUSIC algorithm with narrow band models for the estimation of direction of arrival (DOA) when the source signals are chirps. In this research, we consider wideband models. The joint time-frequency analysis is first used to estimate the chirp rates of the source signals and then the DOA is estimated by the MUSIC algorithm with an iterative approach.
We present an algorithm-based fault tolerant scheme for QR decomposition, that extends the well-known Gentleman-Kung-McWhirter triangular systolic array architecture. Assuming that the array is subject to transient fa...
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ISBN:
(纸本)0819416207
We present an algorithm-based fault tolerant scheme for QR decomposition, that extends the well-known Gentleman-Kung-McWhirter triangular systolic array architecture. Assuming that the array is subject to transient faults, widely separated in time and each affecting a single processor, we give an algorithm that corrects the full triangular array with computational overhead equivalent, on average, to the interpolation of a single extra vector into the data stream.
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.
Originally coined by the sensory psychologist Roger Shepard in the 1960's, chroma transforms frequency into octave equivalence classes. By extending the concept of chroma to chroma strength and how it varies over ...
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Originally coined by the sensory psychologist Roger Shepard in the 1960's, chroma transforms frequency into octave equivalence classes. By extending the concept of chroma to chroma strength and how it varies over time, we have demonstrated the utility of chroma in simplifying the processing and representation of signals dominated by harmonically-related narrowband components. These investigations have utilized an ad hoc procedure for calculating the chromagram from a given time-frequency distribution. The present paper is intended to put this ad hoc procedure on more sound mathematical ground.
Subband-domain algorithms provide an attractive technique for wideband radar array processing. The subband-domain approach decomposes a received wideband signal into a set of narrowband signals. While the number of pr...
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Subband-domain algorithms provide an attractive technique for wideband radar array processing. The subband-domain approach decomposes a received wideband signal into a set of narrowband signals. While the number of processing threads in the system increases, the narrowband signals within each subband can be sampled at a correspondingly slower rate. Therefore, the data rate at the input is similar to that at the output of the subband processor. There are several advantages to the subbanding method. It can simplify typical radar algorithms such as adaptive beamforming and equalization by the virtue of reducing subband signal bandwidth, thereby potentially reducing the computational complexity over an equivalent tapped-delay line approach. It also allows for a greater parallelization of the processing task, hence enabling the use of slower and less power consuming hardware. In order to evaluate the validity of the subbanding approach, it is compared with conventional processing methods. This paper focuses on adaptive beamforming and pulse compression performance for a wideband radar system. The performance of an adaptive beamformer is given for a polyphase filter based subband approach and is measured against narrowband processing. SINR loss curves and beampatterns for a subband system are presented. Design criteria for subband polyphase filter processing that minimizes signal distortion are provided and the distortion is characterized. Finally subband-domain pulse compression is demonstrated and compared with the conventional approach.
This Volume 2 of 2 of the conference proceedings contains 160 papers. Topics discussed include wireless communication and signalprocessing, algorithms for MIMO links, modulation and detection techniques, signal detec...
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This Volume 2 of 2 of the conference proceedings contains 160 papers. Topics discussed include wireless communication and signalprocessing, algorithms for MIMO links, modulation and detection techniques, signal detection and classification, adaptive communications and arrays, image segmentation and frequency domain processing, multiple user/multiple access techniques, digital signalprocessing architectures, hyperspectral processing and multisignals or data fusion, computer arithmetic implementations and FPGA designs, radar and sonar processing, equalization and synchronization techniques, higher order statistical signalprocessing for communications, adaptive signalprocessing in communication, speech coding and processing, wireless systems, special arithmetic techniques, biomedical imaging and advanced modulation and channel estimation.
In this paper, a highly scalable hardware accelerator design for digital signalprocessing is presented. The key features of this accelerator are minimum I/O operations, highly scalable massive parallelism, easy progr...
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ISBN:
(纸本)0819416207
In this paper, a highly scalable hardware accelerator design for digital signalprocessing is presented. The key features of this accelerator are minimum I/O operations, highly scalable massive parallelism, easy programming, and modularity and regularity. With a very large register file (> 1000) per processing element, the reuse factor per datum in this accelerator can be increased significantly (as compared to traditional DSP architectures). System performance is improved because the amount of data transfer between the on-chip cache and the off-chip cache/memory is reduced by the same factor. Since the basic building block of this accelerator is simply a VLSI chip with several processing elements, scalable massive parallelism can be achieved by connecting multiple chips together in a SIMD `vector- like' fashion. Finally, programming of this accelerometer is not difficult because it is operated under the SIMD `vector-like' mode. With the expected VLSI technology in the next few years, the throughput of one single accelerator chip can approach GFLOPs performance. Hence, the high computing power needed by digital signalprocessing applications can be provided by just connecting a small number of this chip together.
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.
The ULV decomposition (ULVD) is an important member of a class of rank-revealing two-sided orthogonal decompositions used to approximate the singular value decomposition (SVD). The ULVD can be updated and downdated mu...
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The ULV decomposition (ULVD) is an important member of a class of rank-revealing two-sided orthogonal decompositions used to approximate the singular value decomposition (SVD). The ULVD can be updated and downdated much faster than the SVD, hence its utility in the solution of recursive total least squares (TLS) problems. However, the robust implementation of ULVD after the addition and deletion of rows (called updating and downdating respectively) is not altogether straightforward. When updating or downdating the ULVD, the accurate computation of the subspaces necessary to solve the TLS problem is of great importance. In this paper, algorithms are given to compute simple parameters that can often show when good subspaces have been computed.
This paper describes a cascade decomposition of the generalized sidelobe canceller (GSC) implementation for linearly constrained minimum variance beamformers. The GSC is initially separated into an adaptive interferen...
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ISBN:
(纸本)0819406945
This paper describes a cascade decomposition of the generalized sidelobe canceller (GSC) implementation for linearly constrained minimum variance beamformers. The GSC is initially separated into an adaptive interference cancellation module followed by a non-adaptive beamformer. We prove that the adaptive interference cancellation module can be decomposed into a cascade of first (or higher) order adaptive interference cancellation modules, where the order corresponds to the number of adaptive degrees of freedom represented in the module. This distributes the computational burden associated with determining the adaptive weights over several lower order problems and facilitates simultaneous implementation of beamformers with differing numbers of adaptive degrees of freedom.
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