We suggest a nonparametric framework for unsupervised learning of projection models in terms of density estimation on quantized sample spaces. The objective is not to optimally re...
— We study the problem of optimal estimation using quantized innovations, with application to distributed estimation over sensor networks. We show that the state probability dens...
Abstract—This paper formulates and studies a general distributed field reconstruction problem using a dense network of noisy one-bit randomized scalar quantizers in the presence...
Lyapunov-Krasowskii functionals are used to design quantized continuous-time control laws for nonlinear systems in the presence of time-invariant pointwise delays in the input. Th...
Quantization-based watermarking schemes are vulnerable to amplitude scaling. Therefore, the scaling factor needs to be estimated at the decoder side, such that the received (attac...