In this paper we consider the direction-of-arrival (DOA) estimation of Gaussian signals in non- Gaussian noise of unknown spatial correlations. The proposed method involves two primary steps. Firstly, the third-order ...
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ISBN:
(纸本)0819416207
In this paper we consider the direction-of-arrival (DOA) estimation of Gaussian signals in non- Gaussian noise of unknown spatial correlations. The proposed method involves two primary steps. Firstly, the third-order cumulant function of the random wavefield received by an array of sensors is estimated and then projected onto the correlation domain to exploit the correlations of noise across the sensors in an array. Secondly, the estimated noise correlation matrix is then utilized in a correlation-based eigenstructure method, such as MUSIC, for DOA estimation. As expected, the proposed method improves the performance of MUSIC which requires the knowledge of noise correlation. Numerical simulation results for both the MUSIC and proposed algorithms are presented and compared.
Following a brief discussion of the potential relevance of chaotic noise models, we consider the problem of separating a signal from an additive mixture with nonlinear noise. The approach we take exploits various prop...
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ISBN:
(纸本)0819416207
Following a brief discussion of the potential relevance of chaotic noise models, we consider the problem of separating a signal from an additive mixture with nonlinear noise. The approach we take exploits various properties of linear filters: their linearity is, of course, important when dealing with additive mixtures of signals, but we also need to understand their effect on nonlinear processes. We describe how FIR and IIR filters differ radically in this respect, and discuss the ways in which each can be used in conjunction with various nonlinear transformations for signal separation.
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.
In this paper we consider cyclostationary signalprocessing techniques implemented via acousto-optics (AO). Cyclic processing methods are reviewed and motivated, including the cyclic correlation and the cyclic spectru...
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ISBN:
(纸本)0819416207
In this paper we consider cyclostationary signalprocessing techniques implemented via acousto-optics (AO). Cyclic processing methods are reviewed and motivated, including the cyclic correlation and the cyclic spectrum. We show how a 1D AO spectrum analyzer can be used to detect the presence, and estimate the value, of cycle frequencies. The cyclic correlation can then be computed at cycle frequencies of interest using a 1D time-integrating correlator. Next we consider the problem of computing the (2D) cyclic correlation for all cycle frequencies and lags simultaneously. This is accomplished via an AO triple-product processor, configured in a manner similar to that used for ambiguity function generation. The cyclic spectrum can be obtained in a post-processing step by Fourier transforming the cyclic correlation in one dimension. We then consider higher order extensions of the cyclic correlation and show how a 2D slice of the 3D cyclic triple-correlation can be computed using an AO four-product processor.
Existing approaches to blind channel estimation and deconvolution (equalization) focus exclusively on channel or inverse-channel impulse response estimation. It is well-known that the quality of the deconvolved output...
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ISBN:
(纸本)0819416207
Existing approaches to blind channel estimation and deconvolution (equalization) focus exclusively on channel or inverse-channel impulse response estimation. It is well-known that the quality of the deconvolved output depends crucially upon the noise statistics also. Typically it is assumed that the noise is white and the signal-to-noise ratio is known. In this paper we remove these restrictions. Both the channel impulse response and the noise model are estimated from the higher-order (fourth, e.g.) cumulant function and the (second-order) correlation function of the received data via a least-squares cumulant/correlation matching criterion. It is assumed that the noise higher-order cumulant function vanishes (e.g., Gaussian noise, as is the case for digital communications). Consistency of the proposed approach is established under certain mild sufficient conditions. The approach is illustrated via simulation examples involving blind equalization of digital communications signals.
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.
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.
Interactions among spontaneous otoacoustic emissions (SOEs), which are narrow-band signals emitted by the cochlea, include the cubic difference tone (CDT) that occurs at frequency 2f 1 - f2 due to the nonlinear coupli...
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ISBN:
(纸本)0819416207
Interactions among spontaneous otoacoustic emissions (SOEs), which are narrow-band signals emitted by the cochlea, include the cubic difference tone (CDT) that occurs at frequency 2f 1 - f2 due to the nonlinear coupling of primary SOEs at f1 and f2. We show that appropriately defined trispectra and tricoherence may be used to detect the CDTs. OAE signals are also characterized by temporal variations in the amplitudes and frequencies;this leads to polynomial phase models, and multiplicative noise processes;we give closed-form expressions for the large sample CRLB for the parameters of the resulting model. We also consider cyclic approaches, and we compare polyperiodogram and periodogram based approaches for the detection of arbitrary frequency coupling laws. Some of the techniques are validated against real data.
We present a new family of architectures for processor arrays to implement Jacobi SVD which allow systolic loading and unloading of input and result matrices. Unlike most of the previous SVD arrays in the literature, ...
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ISBN:
(纸本)0819416207
We present a new family of architectures for processor arrays to implement Jacobi SVD which allow systolic loading and unloading of input and result matrices. Unlike most of the previous SVD arrays in the literature, our architectures do not require special handling of external I/O and hence are closer to the traditional concept of systolic architectures. The boundary processors communicate with the host the same way any of the interior processors communicate with their neighbors. The arrays are surprisingly uniform and simple. The various architectures in the family represent different throughput-hardware tradeoffs corresponding to the degree to which the multiple sweeps have been unrolled and determine the number of independent SVDs which may be pipelined on the array. We achieved systolic loading by using the flexibility provided by the cyclic Jacobi method on the order in which pivot pairs may be chosen. The array operates on the matrix data even as it is being loaded. Once the pipeline is full, the ordering is very similar to odd-even ordering. Our ordering is equivalent to cyclic-by-rows ordering and hence the algorithm is guaranteed to converge. Our systolic loading scheme is very important in an I/O limited system, since it allows more communication to occur in parallel, where the communication includes the loading and unloading operations. The array with the highest throughput in our family of architectures, which implement one-sided Jacobi (either Hestenes' method or Eberlein and Park's method), is a linear array of processors with unidirectional links between neighbors. The architectures with lower throughput require fewer processors connected in a ring, allowing data to recirculate among the processors. The input matrix is loaded one column at a time from the left and the results stream out one column at a time from the right.
Redundant Residue Number Systems (RRNS) have been proposed as suitable candidates for fault tolerance in compute intensive applications. The redundancy is based on multiple projections to moduli sub-sets and conductin...
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ISBN:
(纸本)0819416207
Redundant Residue Number Systems (RRNS) have been proposed as suitable candidates for fault tolerance in compute intensive applications. The redundancy is based on multiple projections to moduli sub-sets and conducting a search for results that lie in a so-called illegitimate range. This paper presents RRNS fault tolerant procedures for a recently introduced finite polynomial ring mapping procedure (modulus replication RNS). The mapping technique dispenses with the need for many relatively prime ring moduli, which is a major draw-back with conventional RRNS systems. Although double, triple, and quadrupole modular redundancy can be implemented in the polynomial mapping structure, polynomial coefficient circuitry, or the independent direct product ring computational channels, for error detection and/or correction, this paper discusses the implementation of redundant rings which are generated by (1) redundant residues, (2) spare general computational channels, or (3) a combination of the two. The first architecture is suitable for RNS embedding in the MRRNS, and the second for single moduli mappings. The combination architecture allows a trade-off between the two extremes. The application area is in fault tolerant compute intensive DSP arrays.
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