Experimental implementation of LMS synthesis of optimum FIR filters with arbitrary time and frequency constraints and noises

Optimum filter theory has nowadays well stated applications in many scientific and technical fields, from communications to biomedical engineering, from nuclear electronics to safety systems, which need accurate estimations of a various number of parameters, extracted from signals detected in noisy environments. The work deals with the experimental implementation of a relaxed constraints fulfillment technique, which allows achieving constraint accomplishments up to the required level of precision, to avoid further and needless degradation in measurement resolution. In particular, the implemented processing technique leads to a class of optimum filters with arbitrary constraints in time and frequency. The implementation has been performed into a digital fully configurable architecture that, in addition to signal generator for emulation of radiation detectors and front-end electronics, also acts as processor of signals from radiation detectors. The experimental implementation has been carried out, tested and fully validated.