@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},