Results 1  10
of
38
The Viterbi algorithm
 Proceedings of the IEEE
, 1973
"... vol. 6, no. 8, pp. 211220, 1951. [7] J. L. Anderson and J. W..Ryon, “Electromagnetic radiation in accelerated systems, ” Phys. Rev., vol. 181, pp. 17651775, 1969. [8] C. V. Heer, “Resonant frequencies of an electromagnetic cavity in an accelerated system of reference, ” Phys. Reu., vol. 134, pp. A ..."
Abstract

Cited by 985 (3 self)
 Add to MetaCart
vol. 6, no. 8, pp. 211220, 1951. [7] J. L. Anderson and J. W..Ryon, “Electromagnetic radiation in accelerated systems, ” Phys. Rev., vol. 181, pp. 17651775, 1969. [8] C. V. Heer, “Resonant frequencies of an electromagnetic cavity in an accelerated system of reference, ” Phys. Reu., vol. 134, pp. A799A804, 1964. [9] T. C. Mo, “Theory of electrodynamics in media in noninertial frames and applications, ” J. Math. Phys., vol. 11, pp. 25892610, 1970.
The Behavior of Convolutional Codes
, 1995
"... It is well known that a convolutional code can be viewed as a linear system over a finite field. In this paper we develop this viewpoint for convolutional codes using several recent innovations from the systems theory literature. In particular we define codes as behaviors of a set of compact support ..."
Abstract

Cited by 63 (17 self)
 Add to MetaCart
It is well known that a convolutional code can be viewed as a linear system over a finite field. In this paper we develop this viewpoint for convolutional codes using several recent innovations from the systems theory literature. In particular we define codes as behaviors of a set of compact support time trajectories over a vector space. We also consider several different representations of codes, in particular generalized first order representations. As an application of these ideas, we present a BCH construction technique for convolutional codes that yields optimal high rate codes.
Algorithmic Complexity in Coding Theory and the Minimum Distance Problem
, 1997
"... We start with an overview of algorithmiccomplexity problems in coding theory We then show that the problem of computing the minimum distance of a binary linear code is NPhard, and the corresponding decision problem is NPcomplete. This constitutes a proof of the conjecture Bedekamp, McEliece, van T ..."
Abstract

Cited by 45 (2 self)
 Add to MetaCart
We start with an overview of algorithmiccomplexity problems in coding theory We then show that the problem of computing the minimum distance of a binary linear code is NPhard, and the corresponding decision problem is NPcomplete. This constitutes a proof of the conjecture Bedekamp, McEliece, van Tilborg, dating back to 1978. Extensions and applications of this result to other problems in coding theory are discussed.
Channel coding: The road to channel capacity
 Proceedings of the IEEE
, 2007
"... ..."
(Show Context)
A System for Face Localization and Facial Feature Extraction
, 1999
"... In this paper we present a way to regard the combined face detection and facial feature extraction problem as an optimization problem. This problem is of too high computational complexity to be of practical use, and we investigate different methods to reduce the complexity. Our proposed system uses ..."
Abstract

Cited by 20 (0 self)
 Add to MetaCart
(Show Context)
In this paper we present a way to regard the combined face detection and facial feature extraction problem as an optimization problem. This problem is of too high computational complexity to be of practical use, and we investigate different methods to reduce the complexity. Our proposed system uses techniques known from the literature (skin colour classifcation, statistical pattern matching, ...) as well as a novel method based on a deformable graph and an extended Viterbi algorithm. Keywords Face localization, Face detection, Facial feature extraction, Modelbased coding, Mpeg4, Face Animation 1 Introduction Localization and tracking of faces and facial features in images and image sequences are important tasks for applications like modelbased coding of video sequences, recognition or identification of faces, and intelligent manmachine interfaces. Although these problems are usually simple tasks for the human visual system, they have proven to be difficult tasks for machinevi...
Design and Implementation of a Low Complexity VLSI TurboCode Decoder Architecture for Low Energy Mobile Wireless
 Communications,” J. VLSI Signal Processing, Feb
"... Abstract. Channel coding is commonly incorporated to obtain sufficient reception quality in wireless mobile communications transceiver to counter channel degradation due to intersymbol interference, multipath dispersion, and thermal noise induced by electronic circuit devices. For low energy mobile ..."
Abstract

Cited by 14 (1 self)
 Add to MetaCart
(Show Context)
Abstract. Channel coding is commonly incorporated to obtain sufficient reception quality in wireless mobile communications transceiver to counter channel degradation due to intersymbol interference, multipath dispersion, and thermal noise induced by electronic circuit devices. For low energy mobile wireless communications, it is highly desirable to incorporate a decoder which has a very low power consumption while achieving a high coding gain. In this paper, a suboptimal lowcomplexity multistage pipeline decoder architecture for a powerful channel coding technique known as “turbocode ” is presented. The presented architecture avoids complex operations such as exponent and logarithmic computations. The turbocode decoding algorithm is reformulated for an efficient VLSI implementation. Furthermore, the communication channel statistic estimation process has been completely eliminated. The architecture has been designed and implemented with the 0.6 „m CMOS standard cell technology using Epoch computer aided design tool. The performance and the circuit complexity of the turbocode decoder are evaluated and compared with the other types of wellknown decoders. The power consumption of the lowcomplexity turbocode decoder is comparable to that of the conventional convolutionalcode decoder. However, the lowcomplexity turbocode decoder has a significant coding gain over the conventional convolutionalcode decoders and it is well suited for very low power applications. 1.
Mathematical Programming Algorithms for RegressionBased Nonlinear Filtering in R^N
 N ,” IEEE Transactions on Signal Processing
, 1999
"... This paper is concerned with regression under a "sum" of partial order constraints. Examples include locally monotonic, piecewise monotonic, runlength constrained, and unimodal and oligomodal regression. These are of interest not only in nonlinear filtering but also in density estimation a ..."
Abstract

Cited by 13 (2 self)
 Add to MetaCart
This paper is concerned with regression under a "sum" of partial order constraints. Examples include locally monotonic, piecewise monotonic, runlength constrained, and unimodal and oligomodal regression. These are of interest not only in nonlinear filtering but also in density estimation and chromatographic analysis. It is shown that under a least absolute error criterion, these problems can be transformed into appropriate finite problems, which can then be efficiently solved via dynamic programming techniques. Although the result does not carry over to least squares regression, hybrid programming algorithms can be developed to solve least squares counterparts of certain problems in the class. Index Terms Dynamic programming, locally monotonic, monotone regression, nonlinear filtering, oligomodal, piecewise monotonic, regression under order constraints, runlength constrained, unimodal. I.
Algebraic Description And Construction Of Error Correcting Codes: A Linear Systems Point Of View
, 1997
"... In this thesis we take a detailed look at the algebraic structure of convolutional and quasicyclic codes using the tools and methods of linear systems theory. Let F q be a finite field with q elements. In particular, we define convolutional codes as linear, right shift invariant, compact support be ..."
Abstract

Cited by 10 (1 self)
 Add to MetaCart
In this thesis we take a detailed look at the algebraic structure of convolutional and quasicyclic codes using the tools and methods of linear systems theory. Let F q be a finite field with q elements. In particular, we define convolutional codes as linear, right shift invariant, compact support behaviors in (F n ) Z+ . We then examine the concepts of observability, controllability, and minimality for convolutional codes as defined above. We show how convolutional codes are dual to the class of autoregressive behaviors. We compare compact support convolutional codes to noncompact support convolutional codes. In addition, we derive first order representations of convolutional codes on a purely module theoretic. We also examine the properties of these representations and give conditions for observability and minimality. Using the systems theoretic structure of convolutional codes we present two code constructions. For the first one we choose n; k; q and ffi 2 Z+ , such that q ffi ...
Properties of the maximum a posteriori path estimator in hidden Markov models
 IEEE Trans. Inform. Theory
, 2006
"... ..."
Fast Digital Locally Monotonic Regression
, 1997
"... Locally monotonic regression is the optimal counterpart of iterated median filtering. In a previous paper, Restrepo and Bovik developed an elegant mathematical framework in which they studied locally monotonic regressions in R N . The drawback is that the complexity of their algorithms is exponen ..."
Abstract

Cited by 7 (1 self)
 Add to MetaCart
Locally monotonic regression is the optimal counterpart of iterated median filtering. In a previous paper, Restrepo and Bovik developed an elegant mathematical framework in which they studied locally monotonic regressions in R N . The drawback is that the complexity of their algorithms is exponential in N . In this paper, we consider digital locally monotonic regressions, in which the output symbols are drawn from a finite alphabet and, by making a connection to Viterbi decoding, provide a fast O(A² ffN ) algorithm that computes any such regression, where jAj is the size of the digital output alphabet, ff stands for lomo degree, and N is sample size. This is linear in N , and it renders the technique applicable in practice.