Editorial Board
Information about the editorial board, steering committee, and advisory board.
Information for Authors
The Â鶹´«Ã½AV Journal on Special Areas in Information Theory (JSAIT) is a multi-disciplinary journal of special issues focusing on the intersections of information theory with fields such as machine learning, statistics, genomics, neuroscience, theoretical computer science, and physics. Any field that utilizes the fundamentals of information theory, including concepts such as entropy, compression, coding, mutual information, divergence, capacity, and rate distortion theory is a candidate for a JSAIT special issue.
Propose a Special Issue
The Â鶹´«Ã½AV Journal on Selected Areas in Information Theory (JSAIT) seeks high quality technical papers on all aspects of Information Theory and its applications. JSAIT is a multi-disciplinary journal of special issues focusing on the intersections of information theory with fields such as machine learning, statistics, genomics, neuroscience, theoretical computer science, and physics.
Hypergraph-Based Source Codes for Function Computation Under Maximal Distortion
This work investigates functional source coding problems with maximal distortion, motivated by approximate function computation in many modern applications. The maximal distortion treats imprecise reconstruction of a function value as good as perfect computation if it deviates less than a tolerance level, while treating reconstruction that differs by more than that level as a failure.
Time-Invariant Prefix Coding for LQG Control
Motivated by control with communication constraints, in this work we develop a time-invariant data compression architecture for linear-quadratic-Gaussian (LQG) control with minimum bitrate prefix-free feedback. For any fixed control performance, the approach we propose nearly achieves known directed information (DI) lower bounds on the time-average expected codeword length. We refine the analysis of a classical achievability approach, which required quantized plant measurements to be encoded via a time-varying lossless source code.