Computing maximum-likelihood bounds on the performance of systems involving partial response (PR) channels, with or without an error correcting code present, is rather complex, requiring exponentiating large matrices of polynomials. Being able to practically and efficiently compute these bounds, especially for cases with data sequences and channels more complex than previously considered cases, is expensive in both computational time and memory used. In this paper, we discuss our implementation of a program to compute these bounds for the case of Reed-Solomon codes over PR channels and explore some of the choices and tradeoffs made in that implementation.

We consider the use of high-rate low-density parity-check (LDPC) codes for magnetic recording. We design and evaluate the performance of a magnetic recording system, which uses an LDPC code as the error-correcting code, in conjunction with a rate 16/17 quasimaximum-transition-run (QMTR) channel code on a modified E/sup 2/PR4 (ME/sup 2/PR4)-equalized channel. Iterative decoding between the partial response channel and the LDPC code is performed. Simulations show that an additional four-dB gain over the QMTR code can be obtained by the LDPC code. The algorithms used to design this LDPC code are also discussed.

Statistical analysis of a fast algorithm for frequency estimation is presented. Details of how the analysis was derived with the aid of a symbolic algebra software package, Maple, are given, and some issues involved in the use of symbolic algebra packages in signal processing research are discussed.>

A new class of fast least squares linear prediction algorithms for frequency estimation is described, and a specific example of this class of algorithms is presented in detail. A simulation for the case of single-sinusoid inputs shows that the estimates are quite sensitive to noise for frequencies near half the Nyquist frequency. A simplified error analysis seems to confirm the existence of the noise sensitivity in that range of frequencies.>