Patent ID: 7054388

Claim:
A signal detection method of searching an input time-series signal for a signal portion similar to a reference time-series signal which is registered in advance and is shorter than the input time-series signal, the method comprising: a reference feature calculating step of obtaining a reference feature time-series signal from the reference time-series signal, where the reference feature time-series signal consists of feature vectors; an input feature calculating step of obtaining an input feature time-series signal from the input time-series signal, where the input feature time-series signal consists of feature vectors; a reference feature coding step of converting the reference feature time-series signal into a reference coded time-series signal consisting of codes which indicate classifications; an input feature coding step of converting the input feature time-series signal into an input coded time-series signal consisting of codes which indicate classifications; a distortion adding step of adding a distortion to at least one of the reference time-series signal, the input time-series signal, the reference feature time-series signal, the input feature time-series signal, the reference coded time-series signal, and the input coded time-series signal; histogram collating step of determining a collation portion in the input coded time-series signal, generating histograms of both the reference coded time-series signal and the collation portion of the input coded time-series signal, and calculating a degree of similarity between the reference coded time-series signal and the collation portion based on the generated histograms; wherein the degree of similarity is compared with a predetermined target degree of similarity, and the histogram collating step is repeatedly executed while changing the collation portion in the input coded time-series signal, thereby determining whether the reference time-series signal is present in the relevant portion of the input time-series signal; and in the distortion adding step: the added distortion is generated using random numbers; an amount of distortion used for distorting features is modeled using a normal distribution, wherein parameters in the modeling are the amount of parallel translation and the variance; and the distortion is added using at least one of the amount of parallel translation and the variance.