Conditional density estimation for physiological control systems

We introduce a connectionist architecture for predicting the conditional probability density for time series prediction in physiological control systems. The mean of the distribution is the target value, and variance is the confidence in the prediction. The methods are verified on a highly nonlinear system that exhibits deterministic chaos, and a brownian motion process that exhibits multimodal behavior.