Effects of convolution on chaotic signals

Because chaotic signals are potentially useful both in describing physical phenomena and in engineering applications, signal processing algorithms exploiting their unique characteristics are of interest. The authors consider issues pertaining to processing signals in convolutional distortion. Specifically, they discuss the effects of convolutional distortion on two parameters commonly used in the description of chaotic signals-the Lyapunov exponents and the fractal dimension of the attractor. In addition, a blind deconvolution technique based on minimizing a nonlinear prediction error for data generated by one-dimensional chaotic maps is presented.<>