On the decoder error probability for Reed-Solomon codes

Upper bounds On the decoder error probability for Reed-Solomon codes are derived. By definition, "decoder error" occurs when the decoder finds a codeword other than the transitted codeword; this is in contrast to "decoder failure," which occurs when the decoder fails to find any codeword at all. These results imply, for example, that for a t error-correcting Reed-Solomon code of length q - 1 over GF(q), if more than t errors occur, the probability of decoder error is less than 1/t!

Node Synchronization for the Viterbi Decoder

Motivated by the needs of NASA's Voyager 2 mission, in this paper we describe an algorithm which detects and corrects losses of node synchronization in convolutionally encoded data. This algorithm, which would be implemented as a hardware device external to a Viterbi decoder, makes statistical decisions about node synch based on the hard-quantized undecoded data stream. We will show that in a worst-case Voyager environment, our method will detect and correct a true loss of synch (thought to be a very rare event) within several hundred bits; many of the resulting outages will be corrected by the outer Reed-Solomon code. At the same time, the mean time between false alarms is on the order of several years, independent of the signal-to-noise ratio

An entropy maximization problem related to optical communication

Motivated by a problem in optical communication, we consider the general problem of maximizing the entropy of a stationary random process that is subject to an average transition cost constraint. Using a recent result of Justenson and Hoholdt, we present an exact solution to the problem and suggest a class of finite state encoders that give a good approximation to the exact solution

PSL-An Expert System to Evaluate Degree Plans

This paper describes a general-purpose expert system to evaluate degree plans according to the individual preferences of a college student. This system implements a preference specification language (PSL) on top of this expert system to allow for the textual expression of certain requirements and preferences that the system uses for evaluation. The PSL evaluator produces a single value to describe how well it meets the student’s preferences, which a plan generation system could use to create a degree plan optimized according to the specification