Information-theory-based analysis of single-molecule time series, inspired by Shannon's studies the information content printed English, can differentiate between Markov (memoryless) and non-Markov signals static dynamic disorder.

An achievable rate for the discrete memoryless relay channel with receiver-transmitter feedback is proposed based on Block-Markov superposition encoding. The achievable rate can also be extended to Gaussian channels. A second achievable rate for the Gaussian relay channel based on a Schalkwijk-Kailath type scheme is presented. For some channels both achievable rates strictly improve upon all pr...

Abstract. We analyze completely the convergence speed of the batch learning algorithm, and compare its speed to that of the memoryless learning algorithm and of learning with memory (as analyzed in [KR2001b]). We show that the batch learning algorithm is never worse than the memoryless learning algorithm (at least asymptotically). Its performance vis-a-vis learning with full memory is less clea...

Given a set of strings, its guesswork is defined as the logarithm of the position at which a string appears in the ordered list of all strings from the most likely to the least likely. Guesswork is central to several applications in information theory: Average guesswork provides a lower bound on the expected computational cost of a sequential decoder to decode successfully the intended message;...

In matrix analysis, the scaling technique reduces chances of an ill-conditioning matrix. This article proposes a one-parameter memoryless Davidon–Fletcher–Powell (DFP) algorithm for solving system monotone nonlinear equations with convex constraints. The measure function that involves all eigenvalues DFP is minimized to obtain parameter’s optimal value. resulting and derivative-free low memory ...