A consensus algorithm for networks with process noise and quantization error
Graph Chatbot
Chat with Graph Search
Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
In this paper, we address the following problem. Given a fixed total number of feedforward and feedback filter taps in a decision feedback equalizer, what is the optimum number of taps of each filter and what is the optimum delay setting? We propose a simp ...
Varied sensory systems use noise in order to enhance detection of weak signals. It has been conjectured in the literature that this effect, known as stochastic resonance, may take place in central cognitive processes such as memory retrieval of arithmetica ...
A simple and complete asymptotical analysis of an optimal piecewise uniform quantization of two-dimensional memoryless Laplacian source with the respect to distortion (D) i.e. the mean-square error (MSE) is presented. Piecewise uniform quantization consist ...
The aim of this paper is to report on recent advances made in global gyrokinetic simulations of ion temperature gradient (ITG) modes and other microinstabilities. The nonlinear development and saturation of ITG modes and the role of E x B zonal flows are s ...
Agentcities is a worldwide initiative designed to help realize the commercial and research potential of agent-based applications by constructing an open distributed network of platforms hosting diverse agents and services. The ultimate aim of the Agentciti ...
This paper addresses the problem of robust exponential filtering for discrete uncertain systems with mixed stochastic and deterministic uncertainties, in addition to unmodelled nonlinearities and measurement and process noises with bounded variances. ...
The first part of this paper proposes an adaptive, data-driven threshold for image denoising via wavelet soft-thresh- olding. The threshold is derived in a Bayesian framework, and the prior used on the wavelet coefficients is the generalized Gaussian distr ...
Signal detection is one of the basic problems in statistical communication theory, and has many applications to contemporary technology, whether in engineering, medical science, or the environment. The most difficult problems are those involving random sig ...
In recent work, it was proposed to use lossy compression to remove noise from corrupted signals, based on the rationale that a reasonable compression method retains the dominant signal features more than the randomness of the noise. To further understand a ...
Particle filtering is now established as one of the most popular methods for visual tracking. Within this framework, there are two important considerations. The first one refers to the generic assumption that the observations are temporally independent giv ...
