Design A Kaiser Window Based Digital Filter by Using GRNN
Abstract
Keywords: ANN, GRNN, LR, MLPFFBP, FDA TOOL
Full Text:
PDFReferences
Haykins S. Neural Networks - A comprehensive foundation. New Delhi: Prentice -Hall of India Private Limited; 2003.
Aggarwal N., Thapar S., Kaur P. Design a low pass FIR low pass filter using particle swarm optimization Based Artificial Neural network, IJETTCS. 2012; 1(4).
Singh J., Singh C. Design of low pass FIR filter by using (GRNN), IJARCSSE. 2013; 3(10).
a. Proakis J.G., Manolakis D.G. Digital Signal Processing – Principle, Algorithms and Applications. New Delhi: Prentice Hall of India; 2000.
Larsen J. Design of Neural Network Filters, Ph.D. Thesis, Electronics Institute, Technical University of Denmark, 1993.
Ahmadand M.O., Wang J.D. An analytical least square solution to the design problem of two-dimensional FIR filters with quadrant ally symmetric or ant symmetric frequency response, IEEE Trans Circ Syst. 1989; CAS-36: 968–79p.
Burrus S., Barrctoand J.A., Selcsnick I.W. Iterative reweighted least-squares design of FIR filters, IEEE Trans Signal Process 1994; 42: 2926–36p.
Tankand W., Hopfield J. Simple neural optimization networks: An A/D converter, signal decision circuit, and a linear programming circuit, IEEE Trans Circ Syst. 1986; CAS-33: 533–41p.
Rabinerand L.R., Gold B. Theory and Application of Digital Signal Processing. Englewood Cliffs, NJ: Prentice-Hall; 1989.
Algaziand R., Suk M. On the frequency weighted least squares design of finite duration filters, IEEE Trans Circ Syst. 1987; CAS-34: 80–95p.
Saramaki I.T. Finite impulse response filter design, In: Handbook for Digital Signal Processing. Mitra S.K., Kaiser J.F., Eds., New York, NY, USA: Wiley; 1993.
Spechtand D.K., Shapiro P.D. Training speed comparison of probabilistic neural networks with back-propagation networks, Proc Int Neural Network Conf. 1990; 1: 440–3p.
Spcclu D.F. Scries estimation of a probability density function, Technimetrics. 1971; 13(2).
Burrascano P. Learning vector quantization for the probabilistic neural network, IEEE Trans Neural Networks. 1991; 2 458–61p.
Cclikoglu H.B. Application of radial basis function and generalized regression neural networks in non-linear utility function specification for travel mode choice modelling, Math Compute Model. 2006; 44: 640–58p.
Tkaczand E.J., Kostas P. An application of wavelet neural network for classification patients with coronary artery disease based on HRV analysis, Proc Ann Int Conf IEEE Eng Med Biol. 2000; 1391–3p.
Demuth H., Beale M. Neural Network Toolbox for Use with MATLAB. User's Guide, Version 3.0.
Specht D.F. A Practical Technique for Estimating General Regression Surfaces. Lockheed Missiles & Space Company, Inc., Palo Alto, CA, LMSC-6-79-68-6, also
DOI: https://doi.org/10.37628/ijmet.v2i1.285
Refbacks
- There are currently no refbacks.