An Innovations Approach to Adaptive Data Compression in Data Transmission

An innovations approach to data compression as a viable method to improve the efficiency of data transmission is proposed. The correlated source is modeled by a ratio of polynomials with slowly time-varying coefficients. Data compression is achieved in three steps by: 1) dithering the source signal with a zero mean white noise process to enable the application of the innovations concept, 2) transforming the dithered signal to an innovations process (correlation removal), and 3) quantizing the resultant innovations process to remove unnecessary fidelity. An adaptive implementation of the data compression system using tapped-delay lines (TDL´s) is obtained using the steepest descent method. Preliminary computer simulation demonstrates that, for binary data transmission, a reduction in mean square signal value of approximately 3 is attained with no observable error at a 31-dB signal-to-noise ratio (SNR).