Patent Document ID: 9852019
Application ID: 14899276
Patent Status: 1

Claim One:
1. A method for use in abnormality detection, the method comprising: providing a plurality of neural network modules; and sequentially training said neural network modules in a cascade order with respect to a set of training data pieces to thereby reduce an error value for each successive neural network module, thereby minimizing an error value with respect to said training data pieces for each successive neural network module in the cascade; wherein said sequentially training comprising: a. providing a first set of calibration data pieces and generating therefrom a first normal behavior map corresponding to said first set of calibration data, b. determining a second set of calibration data pieces which includes calibration data pieces of said first set of calibration data pieces being outside of said first normal behavior map, c. using said second set of calibration data pieces and generating a corresponding second normal behavior map corresponding to said second set of calibration data, d. determining a third set of calibration data pieces including calibration data pieces being outside of said second normal behavior map, e. repeating the process until number of calibration data pieces in a newly generated set satisfies at least one of the following: the number equals to number of calibration data pieces in previous set, or the number is below a predetermined threshold.