@article{(Open Science Index):https://publications.waset.org/pdf/12739, title = {Piecewise Interpolation Filter for Effective Processing of Large Signal Sets}, author = {Anatoli Torokhti and Stanley Miklavcic}, country = {}, institution = {}, abstract = {Suppose KY and KX are large sets of observed and reference signals, respectively, each containing N signals. Is it possible to construct a filter F : KY → KX that requires a priori information only on few signals, p N, from KX but performs better than the known filters based on a priori information on every reference signal from KX? It is shown that the positive answer is achievable under quite unrestrictive assumptions. The device behind the proposed method is based on a special extension of the piecewise linear interpolation technique to the case of random signal sets. The proposed technique provides a single filter to process any signal from the arbitrarily large signal set. The filter is determined in terms of pseudo-inverse matrices so that it always exists.}, journal = {International Journal of Mathematical and Computational Sciences}, volume = {6}, number = {7}, year = {2012}, pages = {770 - 777}, ee = {https://publications.waset.org/pdf/12739}, url = {https://publications.waset.org/vol/67}, bibsource = {https://publications.waset.org/}, issn = {eISSN: 1307-6892}, publisher = {World Academy of Science, Engineering and Technology}, index = {Open Science Index 67, 2012}, }