A fast algorithm for left-to-right HMM decoding is proposed in this paper. The algorithm is developed based on a sequential detection scheme which is asymptotically optimal in the sense of detecting a possible change in distribution as reliably and quickly as possible. The scheme is extended to HMM decoding in determining the state segmentations for likelihood or other score computations. As a ...

A variety of Natural Language Processing (NLP) tasks, such as named entity recognition, stemming and question answering, benefit from knowledge of the words syntactic categories or Partof-Speech (POS) [4][6]. POS taggers have been successfully applied to assign a single best POS to every word in a corpus [2][5][12]. This paper reports on the implementation and empiric comparison of three superv...

This thesis addresses the problem of the high computation complexity issue that arises when decoding hidden Markov models (HMMs) with a large number of states. A novel approach, the two-beam Viterbi, with an extra forward beam, for decoding HMMs is implemented on a system that uses factorial HMM to simultaneously recognize a pair of isolated digits on one audio channel. The two-beam Viterbi alg...

The Performance of the Viterbi algorithm with a new Polya contagion noise process is analyzed. The markov channel is the memory channel usually studied in the bibliography. The Polya channel was introduced years ago as a special case of a memory channel. In this work, the Polya contagion scheme is considered as a noise process and a GaussPolya noise model is introduced this way in order to perf...

Cyclic Redundancy Codes (CRC) code provides a simple, yet powerful, method for the detection of errors during digital data transmission and storage. Convolutional Coding and Decoding (CODEC) is a Forward Error Correction (FEC) technique that is particularly suited for a channel in which the transmitted signal is corrupted mainly by Additive White Gaussian Noise (AWGN). The Viterbi Algorithm (VA...

The growth of information available to learning systems and the increasing complexity of learning tasks determine the need for devising algorithms that scale well with respect to all learning parameters. In the context of supervised sequential learning, the Viterbi algorithm plays a fundamental role, by allowing the evaluation of the best (most probable) sequence of labels with a time complexit...

In wireless communication, the channel state changes repeatedly. In this situation, we select the specification of the Viterbi decoder for the worst case channel state. However, if we select the specification of the Viterbi decoder with such a criterion, the decoder operates inefficiently in the good channel state. In this paper, we propose a specification controllable Viterbi decoder without u...

The Viterbi algorithm is widely used in communications and signal processing. Recently, several area{ e cient architectures for this algorithm have been proposed. Area{e cient architectures trade speed for area by means of mapping the N states of the trellis describing the Viterbi algorithm to P processing elements, where N > P . In this paper a practical VLSI implementation of an area{e cient ...

The wavelet analysis is an e5cient tool for the detection of image edges. Based on the wavelet analysis, we present an unsupervised learning algorithm to detect image edges in this paper. A wavelet domain vector hidden Markov tree (WD-VHMT) is employed in our algorithm to model the statistical properties of multiscale and multidirectional (subband) wavelet coe5cients of an image. With this mode...