Quantized incremental algorithms for distributed optimization
Quantized incremental algorithms for distributed optimization
Wireless sensor networks are capable of collecting an enormous amount of data. Often, the ultimate objective is to estimate a parameter or function from these data, and such estimators are typically the solution of an optimization problem (e.g., maximum likelihood, minimum mean-squared error, or maximum a posteriori). This paper investigates …