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Jelinek, F.

Publications and source records attributed to Jelinek, F..

Tree encoding of Gaussian sources

Tree codes are known to be capable of performing arbitrarily close to the rate-distortion function for any memoryless source and single-letter fidelity criterion. Tree coding and tree search strategies are investigated for the discrete-time memoryless Gaussian source encoded for a signal-power-to-mean-squared-error ratio of about 30 dB (about 5 binary digits per source output). Also, a theoretical lower bound on average search effort is derived. Two code search strategies (the Viterbi algorithm and the stack algorithm) were simulated in assembly language on a large digital computer. After suitable modifications, both strategies yielded encoding with a signal-to-distortion ratio about 1 dB below the limit set by the rate-distortion function. Although this performance is better than that of any previously known instrumentable scheme, it unfortunately requires search computation of the order of 100,000 machine cycles per source output encoded.

Dick, R. J.

Upper bounds on sequential decoding performance parameters

This paper presents the best obtainable random coding and expurgated upper bounds on the probabilities of undetectable error, of t-order failure (advance to depth t into an incorrect subset), and of likelihood rise in the incorrect subset, applicable to sequential decoding when the metric bias G is arbitrary. Upper bounds on the Pareto exponent are also presented. The G-values optimizing each of the parameters of interest are determined, and are shown to lie in intervals that in general have nonzero widths. The G-optimal expurgated bound on undetectable error is shown to agree with that for maximum likelihood decoding of convolutional codes, and that on failure agrees with the block code expurgated bound. Included are curves evaluating the bounds for interesting choices of G and SNR for a binary-input quantized-output Gaussian additive noise channel.

Jelinek, F.

Hybrid coding systems study

The state of efficiency improvement available with high speed decoders presently in operation or under development is summarized. The required ratio of bit-energy-to-noise-density is given in each case for bit error probabilities.

Odenwalder, J. P.

Study of sequential decoding

Sequential decoding problems considered deal with reliable transmission through noise space channels and encoding of space sources for the purpose of data suppression.

Jelinek, F.

Permutation codes for sources.

Source encoding techniques based on permutation codes are investigated. For a broad class of distortion measures it is shown that optimum encoding of a source permutation code is easy to instrument even for very long block lengths. Also, the nonparametric nature of permutation encoding is well suited to situations involving unknown source statistics. For the squared-error distortion measure a procedure for generating good permutation codes of a given rate and block length is described. The performance of such codes for a memoryless Gaussian source is compared both with the rate-distortion function bound and with the performance of various quantization schemes. The comparison reveals that permutation codes are asymptotically ideal for small rates and perform as well as the best entropy-coded quantizers presently known for intermediate rates. They can be made to compare favorably at high rates, too, provided the coding delay associated with extremely long block lengths is tolerable.

Berger, T.

On the structure of rate 1/n convolutional codes.

It is shown what choice there is in assigning output digits to transitions of binary rate 1/n code trellis so that the latter will correspond to a convolutional code. A new upper bound on free distance of rate 1/n convolutional codes is also derived, and the results obtained are used to determine the length of the largest input sequence that can conceivably result in an output whose weight is equal to the free distance of a code of rate 1/2.

Bahl, L.

Study of sequential decoding

Decoding algorithms for data reduction and transmission through noisy space channels using sequential and hybrid computers

Jelinek, F.