This paper proposes a noise-predictive detection algorithm for intersymbol interference channels with linear regressive noise. A block factorization of the covariance matrix of the linear regressive Gaussian noise is ...
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This paper proposes a noise-predictive detection algorithm for intersymbol interference channels with linear regressive noise. A block factorization of the covariance matrix of the linear regressive Gaussian noise is used to derive the branch metrics. This algorithm exhibits near optimal performance. A generalization of this algorithm to signal dependent linear regressive noise is also presented and its performance improvement over conventional algorithms with comparable complexity is shown using simulation results.
Nonintrusive load monitoring technologies are gaining popularity. The authors' proposed approach-a simplified event-detection algorithm based on maximum and minimum points, and a disaggregation method that applies...
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Nonintrusive load monitoring technologies are gaining popularity. The authors' proposed approach-a simplified event-detection algorithm based on maximum and minimum points, and a disaggregation method that applies a simplified viterbi algorithm-saves time and works well for high-power appliances.
A new maneuvering target tracking algorithm is investigated, which is modeled as a class of Markov jump linear systems (MJLS). Drawing on the experience of combination idea of the extended viterbi algorithm (EV) and t...
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A new maneuvering target tracking algorithm is investigated, which is modeled as a class of Markov jump linear systems (MJLS). Drawing on the experience of combination idea of the extended viterbi algorithm (EV) and the interacting multiple model algorithm (IMM), a modular interacting multiple model based on extended viterbi (MIMMEV) is presented. The MIMMEV algorithm consists of N independent interacting multiple model-extended viterbi (IMM-EV). Furthermore, these IMM-EV filters are independent and working in parallel in the MIMMEV algorithm. According to the derived probability, the estimated state of every moment is the weighted sum of each estimator at the corresponding time. Simulation results demonstrate that the proposed algorithm improves the tracking precision and reduces the computational burden compared with traditional IMM and IMM-EV.
Since Chinese characters are composed from a small set of fundamental shapes (radicals) the problem of recognising large numbers of characters can be converted to that of extracting a small number of radicals and then...
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Since Chinese characters are composed from a small set of fundamental shapes (radicals) the problem of recognising large numbers of characters can be converted to that of extracting a small number of radicals and then finding their optimal combination. In this paper, radical extraction is carried out by nonlinear active shape models, in which kernel principal component analysis is employed to capture the nonlinear variation. Treating Chinese character composition as a discrete Markov process, we also propose an approach to recognition with the viterbi algorithm. Our initial experiments are conducted on off-line recognition of 430,800 loosely-con strained characters, comprised of 200 radical categories covering 2154 character categories from 200 writers. The correct recognition rate is 93.5% characters correct (writer-independent). Consideration of published figures for existing radical approaches suggests that our method achieves superior performance. (C) 2002 Elsevier Science B.V. All rights reserved.
We present an algorithm that permits a receiver to calculate the probability of packet error in parallel with the viterbi decoding process. This packet reliability value may be used to request retransmissions in a typ...
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We present an algorithm that permits a receiver to calculate the probability of packet error in parallel with the viterbi decoding process. This packet reliability value may be used to request retransmissions in a type-I hybrid ARQ scheme. It is shown that this scheme can be used to guarantee any required bound on the packet error probability. In addition, this scheme can be used in conjunction with packet combining. The performance of this scheme is compared with that of the Yamamoto-Itoh algorithm and is shown to provide a significant improvement in throughput.
This paper proposes the replacement of the ordinary output probability with its expected value if the addition of noise is modeled as a stochastic process, which in turn is merged with the hidden Markov model (HMM) in...
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This paper proposes the replacement of the ordinary output probability with its expected value if the addition of noise is modeled as a stochastic process, which in turn is merged with the hidden Markov model (HMM) in the viterbi algorithm. This new output probability is analytically derived for the generic case of a mixture of Gaussians and can be seen as the definition of a stochastic version of the weighted viterbi algorithm. Moreover, an analytical expression to estimate the uncertainty in noise canceling is also presented. The method is applied in combination with spectral subtraction to improve the robustness to additive noise of a text-dependent speaker verification system. Reductions as high as 30% or 40% in the error rates and improvements of 50% in the stability of the decision thresholds are reported.
A modified viterbi algorithm for convolutional codes is described that provides for signal-to-noise ratio (SNR) adaptive computational effort. The algorithm has three levels of prioritized effort. Movement from one le...
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A modified viterbi algorithm for convolutional codes is described that provides for signal-to-noise ratio (SNR) adaptive computational effort. The algorithm has three levels of prioritized effort. Movement from one level to the next is controlled by parameters that can be selected according to desired output bit-error-rate performance. For 3-bit soft decision detected signals, coding gain within 0.06 dB of viterbi at 3-dB SNR is achieved for the same constraint-length code with modest parameter values and computational effort. At values of SNR above 6 dB, the algorithm decodes with very low computational effort. Effort levels are controlled by spanning the decoding trellis in steps that are one constraint-length long.
We study the problem of sparse recovery in an overcomplete dictionary. This problem has attracted considerable attention in signal processing, statistics, and computer science, and a variety of algorithms have been de...
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We study the problem of sparse recovery in an overcomplete dictionary. This problem has attracted considerable attention in signal processing, statistics, and computer science, and a variety of algorithms have been developed to recover the sparse vector. We propose a new method based on the computationally efficient viterbi algorithm which is shown to achieve better performance than competing algorithms such as Orthogonal Matching Pursuit (OMP), Orthogonal Least-Squares (OLS), Multi-Branch Matching Pursuit (MBMP), Iterative Hard Thresholding (IHT), and l(1) minimization. We also explore the relationship of the viterbi-based approach with OLS.
An approximate squaring method has been developed for the viterbi algorithm that is faster and more area efficient than conventional exact squaring methods and table look-up. Using Monte-Carlo simulations, it is shown...
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An approximate squaring method has been developed for the viterbi algorithm that is faster and more area efficient than conventional exact squaring methods and table look-up. Using Monte-Carlo simulations, it is shown here that the performance of the viterbi algorithm is not degraded using this approximation. The circuit performance is verified by implementing a 7-b approximate squaring function in a 2-mum CMOS process. It operates at a maximum speed of 20 MHz, consumes 95 pW/Hz of power, and occupies an active area of 380 mum x 650 mum.
The viterbi algorithm, an application of dynamic programming, is widely used for estimation and detection problems in digital communications and signal processing. It is used to detect signals in communication channel...
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The viterbi algorithm, an application of dynamic programming, is widely used for estimation and detection problems in digital communications and signal processing. It is used to detect signals in communication channels with memory, and to decode sequential error-control codes that are used to enhance the performance of digital communication systems. The viterbi algorithm is also used in speech and character recognition tasks where the speech signals or characters are modeled by hidden Markov models. The article explains the basics of the viterbi algorithm as applied to systems in digital communication systems, and speech and character recognition. It also focuses on the operations and the practical memory requirements to implement the viterbi algorithm in real-time.< >
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