Distributed Functional Scalar Quantization Simplified

Distributed functional scalar quantization (DFSQ) theory provides optimality conditions and predicts performance of data acquisition systems in which a computation on acquired data is desired. We address two limitations of previous works: prohibitively expensive decoder design and a restriction to sources with bounded distributions. We rigorously show that a much simpler decoder has equivalent asymptotic performance as the conditional expectation estimator previously explored, thus reducing decoder design complexity. The simpler decoder has the feature of decoupled communication and computation blocks. Moreover, we extend the DFSQ framework with the simpler decoder to acquire sources with infinite-support distributions such as Gaussian or exponential distributions. Finally, through simulation results we demonstrate that performance at moderate coding rates is well predicted by the asymptotic analysis, and we give new insight on the rate of convergence

Distributed Scalar Quantization for Computing: High-Resolution Analysis and Extensions

Communication of quantized information is frequently followed by a computation. We consider situations of \emph{distributed functional scalar quantization}: distributed scalar quantization of (possibly correlated) sources followed by centralized computation of a function. Under smoothness conditions on the sources and function, companding scalar quantizer designs are developed to minimize mean-squared error (MSE) of the computed function as the quantizer resolution is allowed to grow. Striking improvements over quantizers designed without consideration of the function are possible and are larger in the entropy-constrained setting than in the fixed-rate setting. As extensions to the basic analysis, we characterize a large class of functions for which regular quantization suffices, consider certain functions for which asymptotic optimality is achieved without arbitrarily fine quantization, and allow limited collaboration between source encoders. In the entropy-constrained setting, a single bit per sample communicated between encoders can have an arbitrarily-large effect on functional distortion. In contrast, such communication has very little effect in the fixed-rate setting.Comment: 36 pages, 10 figure

Not Available

Not AvailableThere is a definitive need to increase the fish production for future through sustainable ways towards alleviating the issues concerning food security, livelihood and employment. Indian fisheries sector faces one of its utmost looming challenges to increase the fish production, to diversify the culture practices and to empower the farming communities by providing sustainable livelihood and employment. Mariculture is an important sub sector in aquaculture that contributes significantly to the global food security, however has met serious challenges in Andaman and Nicobar Islands. Open sea cage culture is a potential sub sector in mariculture that holds greater prospective towards livelihood and employment in addition to its contributory role in food security. There is an absolute need to address the issues governing the development of open sea cage sector which demands a comprehensive roadmap and suitable policy directives with guiding principles. The attempted policy brief in collaboration with various scientific and development departments aim to address the prevailing issues with potential solutions and innovative approaches in engagement with the depending stakeholders. We strongly believe that the policy brief could be a ready reckoner for policy makers and will play a greater role in development of open sea cage culture sector in the Islands.Not Availabl