channel is a varying binary symmetric channel with crossover probabilities determined by a binary-state Markov process. In general, such a channel has a memory that depends on the transition probabilities between the states. First, a method of calculating the capacity of this channel is introduced and applied to several examples: then the question of coding is addressed. In the conventional usage of varying channels, a code suitable for memoryless channels is used in conjunction with an interleaver, with the decoder considering the deinterleaved symbol stream as the output of a derived memoryless channel. The transmission rate in such uses is limited by the capacity of this memoryless channel, which is, however, often considerably less than the capacity of the original channel. In this work a decision-feedback decoding algorithm, that completely recovers this capacity loss, is introduced. It is shown that the performance of a system incorporating such an algorithm is determined by an equivalent genie-aided channel, the capacity of which equals that of the original channel. Also, the calculated random coding exponent of the genie-aided channel indicates a considerable increase in the cutoff rate over the conventionally derived memoryless channel. 'Strictly speaking, at any rate below _C [2, pp. 180z181]. The Gilbert-Elliott channel is indecomposable and therefore _C = C = C [2, p. 1091.

No abstract

Recent developments of automated methods for monitoring animal movement, e.g., global positioning systems (GPS) technology, yield high-resolution spatiotemporal data. To gain insights into the processes creating movement patterns, we present two new techniques for extracting information from these data on repeated visits to a particular site or patch ("recursions"). Identification of such patches and quantification of recursion pathways, when combined with patch-related ecological data, should contribute to our understanding of the habitat requirements of large herbivores, of factors governing their space-use patterns, and their interactions with the ecosystem.We begin by presenting output from a simple spatial model that simulates movements of largeherbivore groups based on minimal parameters: resource availability and rates of resource recovery after a local depletion. We then present the details of our new techniques of analyses (recursion analysis and circle analysis) and apply them to data generated by our model, as well as two sets of empirical data on movements of African buffalo (Syncerus caffer): the first collected in Klaserie Private Nature Reserve and the second in Kruger National Park, South Africa.Our recursion analyses of model outputs provide us with a basis for inferring aspects of the processes governing the production of buffalo recursion patterns, particularly the potential influence of resource recovery rate. Although the focus of our simulations was a comparison of

No abstract

No abstract