This paper presents distributed bounded-error parameter and state estimation algorithms suited to measurement processing by a network of sensors. Contrary to centralized estimation...
—Designing efficient scheduling algorithms is an important problem in a general class of networks with resourcesharing constraints, such as wireless networks and stochastic proc...
Information in the nervous system has often been considered as being represented by simultaneous discharge of a large set of neurons. We propose a learning mechanism for neural inf...
In this paper, a method is introduced how to process the Discrete Fourier Transform (DFT) by a singlelayer neural network with a linear transfer function. By implementing the sugg...
One of the primary advantages of artificial neural networks is their inherent ability to perform massively parallel, nonlinear signal processing. However, the asynchronous dynamics...