Cascade Structure for Finite Impulse Response Filters and Linear Prediction

Article Sidebar

PDF (Spanish) PDF
Published: Dec 30, 2012
DOI: https://doi.org/10.17163/ings.n8.2012.03
Keywords:
Cascade structures, Finite impulse response filters, Transversal filters, Linear estimation, LMS algorithm, RLS algorithm.

Main Article Content

Walter Humberto Orozco Tupacyupanqui

Abstract

This paper presents a complete analysis of the cascade structure for adaptive transversal filters based on adaptive algorithms. The standard structure of the cascade transversal FIR filter is obtained by replacing the whole structure by small ones with the same impulse response but having a less number of taps than the original structure. Computer simulation result shows the validity, reliability and the limitations that the model could have in its capacity of prediction. The optimal values of the model are compared with those obtained by the standard least mean square and recursive least square adaptive algorithms in order to verify the convergence of the weights and determine how fast this structure achieves those weights. For this case the speed of the algorithm is determined by the number of iterations that the filter requires to reach the minimum square value of its learning curve.

Article Details

Issue
No. 8 (2012): July / December
Section
Scientific Paper

 

The Universidad Politécnica Salesiana of Ecuador preserves the copyrights of the published works and will favor the reuse of the works. The works are published in the electronic edition of the journal under a Creative Commons Attribution/Noncommercial-No Derivative Works 4.0 Ecuador license: they can be copied, used, disseminated, transmitted and publicly displayed.

The undersigned author partially transfers the copyrights of this work to the Universidad Politécnica Salesiana of Ecuador for printed editions.

It is also stated that they have respected the ethical principles of research and are free from any conflict of interest. The author(s) certify that this work has not been published, nor is it under consideration for publication in any other journal or editorial work.

The author (s) are responsible for their content and have contributed to the conception, design and completion of the work, analysis and interpretation of data, and to have participated in the writing of the text and its revisions, as well as in the approval of the version which is finally referred to as an attachment.

Author Biography

Walter Humberto Orozco Tupacyupanqui

Máster en Ciencias en Ingeniería Eléctrica y Sistemas, Ingeniero Eléctrico, Estudiante de Doctorado en Comunicaciones y Electrónica de la Sección de Estudios de Posgrado e Investigación del Instituto Politécnico Nacional de México. Docente de la carrera de Ingeniería Eléctrica y Electrónica de la Universidad Politécnica Salesiana, sede Cuenca.

References

B. Widrow and S. Stearns, Adaptive signal processing, 1st ed. Englewood Cliffs, NJ: Prentice-Hall, Inc, 1985.

L. Sibul, Adaptive signal processing, 1st ed. New York: IEEE press, 1987.

A. Sayed, Adaptive filters, 1st ed. New Jersey: Wiley-IEEE Press, 2008. 4] L. B. Jackson and S. L. Wood, “Linear prediction in cascade form,” IEEE Transactions on Acoustics, Speech and Signal Processing, vol. 26, no. 6, pp. 518–528, 1978.

P. Prandoni and M. Vetterli, “An FIR cascade structure for adaptive linear prediction,” IEEE Transactions on Signal Processing, vol. 46, no. 9, pp. 2566–2571, 1998.

W. Orozco, “A cascade predictor filter of one-tap stages for adaptive linear prediction,” Dec. 2005, Final project, New York Institute of Technology, Old Westbury, The United States.

J. Martinez and K. Nakano, “Cascade lattice IIR adaptive filter structure using simultaneous perturbation method for self-adjusting SHARF algorithm,” in SICE Annual Conference, 2008. IEEE, 2008, pp. 2156–2161.

D. Shi and Y. Yu, “Design of discrete-valued linear phase FIR filters in cascade form,” IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 58, no. 7, pp. 1627–1636, 2011.

R. Patnaik, V. Vandrasi, C. Madsen, A. Eftekhar, and A. Adibi, “Comparison of cascade, lattice, and parallel filter architectures,” Journal of Lightwave Technology,, vol. 28, no. 23, pp. 3463–3469, 2010.

H. N. Apolo Castillo and A. E. Córdova Medina, “Modelación matemática y simulación de un filtro digital híbrido FIR adaptativo lineal óptimo,” 2010, Proyecto de graduación, Universidad Politécnica Salesiana, Cuenca, Ecuador.

A. Sayed, Fundamentals of adaptive filtering, 1st ed. New Jersey: Wiley-IEEE Press, 2003.