Wavelet neural network algorithms with applications in approximation signals

Carlos Roberto Domínguez Mayorga; María Angélica Espejel Rivera; Luis Enrique Ramos Velasco; Julio Cesar Ramos Fernández; Enrique Escamilla Hernández

doi:10.1007/978-3-642-25330-0_33

Wavelet neural network algorithms with applications in approximation signals

Carlos Roberto Domínguez Mayorga, María Angélica Espejel Rivera, Luis Enrique Ramos Velasco, Julio Cesar Ramos Fernández, Enrique Escamilla Hernández

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

In this paper we present algorithms which are adaptive and based on neural networks and wavelet series to build wavenets function approximators. Results are shown in numerical simulation of two wavenets approximators architectures: the first is based on a wavenet for approach the signals under study where the parameters of the neural network are adjusted online, the other uses a scheme approximators with an IIR filter in the output of wavenet, which helps to reduce convergence time to a minimum time desired.

Original language	English
Title of host publication	Advances in Soft Computing - 10th Mexican International Conference on Artificial Intelligence, MICAI 2011, Proceedings
Pages	374-385
Number of pages	12
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-642-25330-0_33
State	Published - 2011
Externally published	Yes
Event	10th Mexican International Conference on Artificial Intelligence, MICAI 2011 - Puebla, Mexico Duration: 26 Nov 2011 → 4 Dec 2011

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	7095 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	10th Mexican International Conference on Artificial Intelligence, MICAI 2011
Country/Territory	Mexico
City	Puebla
Period	26/11/11 → 4/12/11

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10.1007/978-3-642-25330-0_33

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Domínguez Mayorga, C. R., Espejel Rivera, M. A., Ramos Velasco, L. E., Ramos Fernández, J. C., & Escamilla Hernández, E. (2011). Wavelet neural network algorithms with applications in approximation signals. In Advances in Soft Computing - 10th Mexican International Conference on Artificial Intelligence, MICAI 2011, Proceedings (PART 2 ed., pp. 374-385). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7095 LNAI, No. PART 2). https://doi.org/10.1007/978-3-642-25330-0_33

Domínguez Mayorga, Carlos Roberto ; Espejel Rivera, María Angélica ; Ramos Velasco, Luis Enrique et al. / Wavelet neural network algorithms with applications in approximation signals. Advances in Soft Computing - 10th Mexican International Conference on Artificial Intelligence, MICAI 2011, Proceedings. PART 2. ed. 2011. pp. 374-385 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

@inproceedings{ce83f246e0cf4512962ba03b9b58eb2b,

title = "Wavelet neural network algorithms with applications in approximation signals",

abstract = "In this paper we present algorithms which are adaptive and based on neural networks and wavelet series to build wavenets function approximators. Results are shown in numerical simulation of two wavenets approximators architectures: the first is based on a wavenet for approach the signals under study where the parameters of the neural network are adjusted online, the other uses a scheme approximators with an IIR filter in the output of wavenet, which helps to reduce convergence time to a minimum time desired.",

author = "{Dom{\'i}nguez Mayorga}, {Carlos Roberto} and {Espejel Rivera}, {Mar{\'i}a Ang{\'e}lica} and {Ramos Velasco}, {Luis Enrique} and {Ramos Fern{\'a}ndez}, {Julio Cesar} and {Escamilla Hern{\'a}ndez}, Enrique",

year = "2011",

doi = "10.1007/978-3-642-25330-0_33",

language = "Ingl{\'e}s",

isbn = "9783642253294",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

number = "PART 2",

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booktitle = "Advances in Soft Computing - 10th Mexican International Conference on Artificial Intelligence, MICAI 2011, Proceedings",

edition = "PART 2",

note = "10th Mexican International Conference on Artificial Intelligence, MICAI 2011 ; Conference date: 26-11-2011 Through 04-12-2011",

}

Domínguez Mayorga, CR, Espejel Rivera, MA, Ramos Velasco, LE, Ramos Fernández, JC & Escamilla Hernández, E 2011, Wavelet neural network algorithms with applications in approximation signals. in Advances in Soft Computing - 10th Mexican International Conference on Artificial Intelligence, MICAI 2011, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 7095 LNAI, pp. 374-385, 10th Mexican International Conference on Artificial Intelligence, MICAI 2011, Puebla, Mexico, 26/11/11. https://doi.org/10.1007/978-3-642-25330-0_33

Wavelet neural network algorithms with applications in approximation signals. / Domínguez Mayorga, Carlos Roberto; Espejel Rivera, María Angélica; Ramos Velasco, Luis Enrique et al.
Advances in Soft Computing - 10th Mexican International Conference on Artificial Intelligence, MICAI 2011, Proceedings. PART 2. ed. 2011. p. 374-385 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7095 LNAI, No. PART 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Wavelet neural network algorithms with applications in approximation signals

AU - Domínguez Mayorga, Carlos Roberto

AU - Espejel Rivera, María Angélica

AU - Ramos Velasco, Luis Enrique

AU - Ramos Fernández, Julio Cesar

AU - Escamilla Hernández, Enrique

PY - 2011

Y1 - 2011

N2 - In this paper we present algorithms which are adaptive and based on neural networks and wavelet series to build wavenets function approximators. Results are shown in numerical simulation of two wavenets approximators architectures: the first is based on a wavenet for approach the signals under study where the parameters of the neural network are adjusted online, the other uses a scheme approximators with an IIR filter in the output of wavenet, which helps to reduce convergence time to a minimum time desired.

AB - In this paper we present algorithms which are adaptive and based on neural networks and wavelet series to build wavenets function approximators. Results are shown in numerical simulation of two wavenets approximators architectures: the first is based on a wavenet for approach the signals under study where the parameters of the neural network are adjusted online, the other uses a scheme approximators with an IIR filter in the output of wavenet, which helps to reduce convergence time to a minimum time desired.

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DO - 10.1007/978-3-642-25330-0_33

M3 - Contribución a la conferencia

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BT - Advances in Soft Computing - 10th Mexican International Conference on Artificial Intelligence, MICAI 2011, Proceedings

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Domínguez Mayorga CR, Espejel Rivera MA, Ramos Velasco LE, Ramos Fernández JC, Escamilla Hernández E. Wavelet neural network algorithms with applications in approximation signals. In Advances in Soft Computing - 10th Mexican International Conference on Artificial Intelligence, MICAI 2011, Proceedings. PART 2 ed. 2011. p. 374-385. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-25330-0_33

Wavelet neural network algorithms with applications in approximation signals

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