We introduce a new regression framework, Gaussian process regression networks (GPRN), which combines the structural properties of Bayesian neural networks with the nonparametric flexibility of Gaussian processes. This model accommodates input dependent signal and noise correlations between multiple response variables, input dependent length-scales and amplitudes, and heavy-tailed predictive dis...

In recent years, there has been considerable interest in the use of CDMA in mobile communications. Bit error rate is one of the most important parameters in the evaluation of CDMA systems. In this paper, we develop a technique to find an accurate approximation to the probability of bit error for asynchronous direct–sequence code division multiple–access (DS/CDMA) systems by modeling the multipl...