Modifying real convolutional codes for protecting digital filtering systems

A method is presented for protecting the overall realization of digital filters implemented with very dense high-speed electronic devices against both hard and soft errors at the data sample level using the error-detecting properties of real convolutional codes. The normal filter system is surrounded with parallel parity channels defined by a real systematic rate k/n convolutional code. Erroneous behavior is detected by comparing externally the calculated and regenerated parity samples. Significant complexity reductions are possible by modifying the code structure, without loss of error protection, yielding simplified parity channels with finite impulse response (FIR) structures with computational rates decimated by k . The code modification procedure is described. The code modification process has been automated in a computer algorithm. The effects of parity filter quantizations are analyzed and a bound on the mean-square error in the parity comparison is given