US 5,400,371 A · System and method for filtering random noise using data compression

Abstract

In a system in which a non-random, noise-free signal is disturbed by random noise, one first determines a way to measure the difference between two signals, and one also selects a measure of complexity for signals. Based on a series of discrete values of the noisy signal, a compression processor generates a series of compressed signals representing the noisy signal, each within a corresponding error or loss tolerance of the discrete values of the noisy signal. An optimization processor applies the various loss tolerance values to the compression processor and then evaluates the relative complexity of the corresponding compressed signals. The optimization processor then determines an optimal knee point loss tolerance, below which the complexity of the compressed signals rises rapidly. For continued filtering of the noisy signal, the compression processor compresses the noisy signal using the optimal knee point loss tolerance. The optimally compressed signals are then passed to a decompression processor, which generates a filtered signal corresponding to the noisy signal. In certain embodiments, the optimization processor also controls the sampling rate of the noisy signal; this makes possible a reduction in the residual loss of the filtered signal.

Claims11

Dependent claims

A system for filtering a noisy signal, which includes a desired signal corrupted by random noise, comprising:

A. a source of discrete samples of the noisy signal;
B. a compression processor having, as an uncompressed input, the discrete samples of the noisy signal, and having as a compressed output a compressed representation of an approximation signal that differs from the uncompressed input by no more than an adjustable error tolerance, which is a predetermined function of a predetermined error metric and is smaller than the uncompressed input in a predetermined complexity measure;
C. a decompression processor having the compressed representation of the approximation signal as a compressed input and having the approximation signal as a decompressed output;
and
D. an optimization processor that has:
1. an optimization input connected to the compressed output of the compression processor to receive the compressed representation of the approximation signal;
and
2. a tolerance output connected to the compression processor and conveying the adjustable error tolerance of the compression processor.

5 more elements

A method for filtering a noisy signal, which includes a desired signal corrupted by random noise, comprising the following steps:

A. selecting an error metric and a complexity measure;
B. for each of a plurality of error tolerance values, repeating steps C-E as follows:
C. selecting one of the error tolerance values;
D. in a compression processor, generating a compressed data signal that differs from the noisy signal by no more than the selected error tolerance value according to the selected error metric;
E. in an optimization processor, for each generated compressed data signal, calculating a corresponding complexity value using the selected complexity measure;
F. determining a knee-point error tolerance value as the value at which the complexity values have maximum acceleration with respect to the error tolerance value;
G. setting a running error tolerance rate for the compression processor equal to the knee-point error tolerance value;
and
H. filtering the noisy signal by compressing it in the compression processor with the running error tolerance rate, and decompressing it in a decompression processor.

6 more elements

Dependencies are inferred from the claim text.

System and method for filtering random noise using data compression

Life of this patent

System and method for filtering random noise using data compression

Life of this patent

Abstract

Claims11