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AC-4 is a state-of-the-art audio codec standardized in ETSI (TS 103 190 and TS 103 190-2) and included in the DVB toolbox (TS 101 154 V2.2.1 and DVB BlueBook A157) and, at the time of writing, is a candidate standard for ATSC 3.0 as per A/342 part 2. AC-4 is an audio codec designed to address the current and future needs of video and audio entertainment services, including broadcast and Internet streaming. As such, it incorporates a number of features beyond the traditional audio coding algorithms, such as capabilities to support immersive and personalized audio, support for advanced loudness management, video-frame synchronous coding, dialog enhancement, etc. This paper will outline the thinking behind the design of the AC-4 codec, explain the different coding tools used, the systemic features included, and give an overview of performance and applications. It further outlines metadata aspects (immersive and personalized, essential for broadcast), metadata carriage, aspects of interchange of immersive programing, as well as immersive playback and rendering. [ABSTRACT FROM AUTHOR]

In his seminal paper published in 2002, Passino pointed out how individual and groups of bacteria forage nutrients and how to model it as a distributed optimization process, which he called the bacterial foraging optimization algorithm (BFOA). One of the major driving forces of BFOA is the chemotactic movement of a virtual bacterium that models a trial solution of the optimization problem. This paper presents mathematical analysis of the chemotactic step in BFOA from the viewpoint of the classical gradient descent search. The analysis points out that "the chemotaxis employed by classical BFOA usually results in sustained oscillation, especially on flat fitness landscapes, when a bacterium cell is close to the optima. To accelerate the convergence speed of the group of bacteria near the global optima, two simple schemes for adapting the chemotactic step height have been proposed. Computer simulations over several numerical benchmarks indicate that BFOA with the adaptive chemotactic operators shows better convergence behavior, compared to the classical BFOA. The paper finally investigates an interesting application of the proposed adaptive variants of BFOA to the frequency-modulated sound wave synthesis problem, appearing in the field of communication engineering. [ABSTRACT FROM AUTHOR]

-Bacterial-foraging optimization algorithm (BFOA) attempts to model the individual and group behavior of E.Coli bacteria as a distributed optimization process. Since its inception, BFOA has been finding many important applications in real-world optimization problems from diverse domains of science and engineering. One key step in BFOA is the computational chemotaxis, where a bacterium (which models a candidate solution of the optimization problem) takes steps over the foraging landscape in order to reach regions with high-nutrient content (corresponding to higher fitness). The simulated chemotactic movement of a bacterium may be viewed as a guided random walk or a kind of stochastic hill climbing from the viewpoint of optimization theory. In this paper, we first derive a mathematical model for the chemotactic movements of an artificial bacterium living in continuous time. The stability and convergence-behavior of the said dynamics is then analyzed in the light of Lyapunov stability theorems. The analysis indicates the necessary bounds on the chemotactic step-height parameter that avoids limit cycles and guarantees convergence of the bacterial dynamics into an isolated optimum. Illustrative examples as well as simulation results have been provided in order to support the analytical treatments. [ABSTRACT FROM AUTHOR]