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Design of reservoir computing systems for the recognition of noise corrupted speech and handwriting

(2015)
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(UGent) and (UGent)
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Keywords
reservoir computing network, acoustic modeling, speech recognition

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  • 2015.02.27 - Azarakhsh Jalalvand - Design of Reservoir Computing Systems for the Recognition of Noise-Corrupted Speech and Handwriting.pdf
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Citation

Please use this url to cite or link to this publication:

MLA
Jalalvand, Azarakhsh. “Design of Reservoir Computing Systems for the Recognition of Noise Corrupted Speech and Handwriting.” 2015 : n. pag. Print.
APA
Jalalvand, A. (2015). Design of reservoir computing systems for the recognition of noise corrupted speech and handwriting. Ghent University. Faculty of Engineering and Architecture, Ghent, Belgium.
Chicago author-date
Jalalvand, Azarakhsh. 2015. “Design of Reservoir Computing Systems for the Recognition of Noise Corrupted Speech and Handwriting”. Ghent, Belgium: Ghent University. Faculty of Engineering and Architecture.
Chicago author-date (all authors)
Jalalvand, Azarakhsh. 2015. “Design of Reservoir Computing Systems for the Recognition of Noise Corrupted Speech and Handwriting”. Ghent, Belgium: Ghent University. Faculty of Engineering and Architecture.
Vancouver
1.
Jalalvand A. Design of reservoir computing systems for the recognition of noise corrupted speech and handwriting. [Ghent, Belgium]: Ghent University. Faculty of Engineering and Architecture; 2015.
IEEE
[1]
A. Jalalvand, “Design of reservoir computing systems for the recognition of noise corrupted speech and handwriting,” Ghent University. Faculty of Engineering and Architecture, Ghent, Belgium, 2015.
@phdthesis{5903235,
  author       = {Jalalvand, Azarakhsh},
  isbn         = {9789085787679},
  keywords     = {reservoir computing network,acoustic modeling,speech recognition},
  language     = {eng},
  pages        = {XXXVIII, 215},
  publisher    = {Ghent University. Faculty of Engineering and Architecture},
  school       = {Ghent University},
  title        = {Design of reservoir computing systems for the recognition of noise corrupted speech and handwriting},
  year         = {2015},
}