Concavity of Mutual Information Rate for Input-Restricted Finite-State Memoryless Channels at High SNR

We consider a finite-state memoryless channel with i.i.d. channel state and the input Markov process supported on a mixing finite-type constraint. We discuss the asymptotic behavior of entropy rate of the output hidden Markov chain and deduce that the mutual information rate of such a channel is concave with respect to the parameters of the input Markov processes at high signal-to-noise ratio. In principle, the concavity result enables good numerical approximation of the maximum mutual information rate and capacity of such a channel.Comment: 26 page

Analyticity of Entropy Rate of Hidden Markov Chains

We prove that under mild positivity assumptions the entropy rate of a hidden Markov chain varies analytically as a function of the underlying Markov chain parameters. A general principle to determine the domain of analyticity is stated. An example is given to estimate the radius of convergence for the entropy rate. We then show that the positivity assumptions can be relaxed, and examples are given for the relaxed conditions. We study a special class of hidden Markov chains in more detail: binary hidden Markov chains with an unambiguous symbol, and we give necessary and sufficient conditions for analyticity of the entropy rate for this case. Finally, we show that under the positivity assumptions the hidden Markov chain {\em itself} varies analytically, in a strong sense, as a function of the underlying Markov chain parameters.Comment: The title has been changed. The new main theorem now combines the old main theorem and the remark following the old main theorem. A new section is added as an introduction to complex analysis. General principle and an example to determine the domain of analyticity of entropy rate have been added. Relaxed conditions for analyticity of entropy rate and the corresponding examples are added. The section about binary markov chain corrupted by binary symmetric noise is taken out (to be part of another paper

Derivatives of Entropy Rate in Special Families of Hidden Markov Chains

Consider a hidden Markov chain obtained as the observation process of an ordinary Markov chain corrupted by noise. Zuk, et. al. [13], [14] showed how, in principle, one can explicitly compute the derivatives of the entropy rate of at extreme values of the noise. Namely, they showed that the derivatives of standard upper approximations to the entropy rate actually stabilize at an explicit finite time. We generalize this result to a natural class of hidden Markov chains called ``Black Holes.'' We also discuss in depth special cases of binary Markov chains observed in binary symmetric noise, and give an abstract formula for the first derivative in terms of a measure on the simplex due to Blackwell.Comment: The relaxed condtions for entropy rate and examples are taken out (to be part of another paper). The section about general principle and an example to determine the domain of analyticity is taken out (to be part of another paper). A section about binary Markov chains corrupted by binary symmetric noise is adde

Mean sensitive, mean equicontinuous and almost periodic functions for dynamical systems

We show that an $R^d$-topological dynamical system equipped with an invariant ergodic measure has discrete spectrum if and only it is $\mu$-mean equicontinuous (proven for $Z^d$ before). In order to do this we introduce mean equicontinuity and mean sensitivity with respect to a function. We study this notion in the topological and measure theoretic setting. In the measure theoretic case we characterize almost periodic functions and in the topological case we show that weakly almost periodic functions are mean equicontinuous (the converse does not hold)

COMPETENCE ACQUISITION IN RETAIL FOOD: EFFICIENT CONSUMER RESPONSE AND ENVIRONMENTAL MANAGEMENT

Based on interviews with retail food store managers and a subsequent survey, this paper traces the pathways that spawn competence acquisition in the retail food industry. It finds that having an essential capability for learning, that is, obtaining new ideas, concepts, methods, tends to breed competencies in a number of areas which are of both business and social significance. In this study, the capacity of this essential capability to generate competencies in efficient consumer response (ECR) and environmental management (EM) are examined. These competencies have attracted the attention of the retail food industry in its efforts to become more competitive with alternative retail food channels. The results show that firms possessing the essential capability of generating new ideas are more likely to have higher sales per square foot. Ties with suppliers lead to higher sales per square foot through improved environmental practices and more consumer education. Technical assistance helps retail grocers acquire a social competence in environmental management.Agribusiness, Environmental Economics and Policy, Industrial Organization, Marketing,