Residual Correlation of the Hadamard Transforms of Stationary Markov-1 Signals

The residual correlation of the Hadamard transforms of stationary Markov-1 signals is investigated. It is shown that the decorrelation in the Hadamard domain is not substantially improved by increasing the block size or the number of data points. This is in sharp contrast with the DFT and other sinusoidal transforms known for their asymptotic equivalence to the KLT. The computational simplicity of the Hadamard transform is counterbalanced by its poor decorrelating capability. Comparison of the Hadamard and Fourier transforms in their decorrelating performance is included.