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A Method for Designing FIR Filters with Arbitrary Magnitude Characteristic Used for Modeling Human AudiogramSZOPOS, E. , NEAG, M. , SARACUT, I. , HEDESIU, H. , FESTILA, L.
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discrete Fourier transforms, error analysis, FIR filter, interpolation and non-uniform sampling
digital(7), filter(6), design(5), systems(4), circuits(4)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2012-05-30
Volume 12, Issue 2, Year 2012, On page(s): 51 - 56
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2012.02009
Web of Science Accession Number: 000305608000009
SCOPUS ID: 84865294072
This paper presents an iterative method for designing FIR filters that implement arbitrary magnitude characteristics, defined by the user through a set of frequency-magnitude points (frequency samples). The proposed method is based on the non-uniform frequency sampling algorithm. For each iteration a new set of frequency samples is generated, by processing the set used in the previous run; this implies changing the samples location around the previous frequency values and adjusting their magnitude through interpolation. If necessary, additional samples can be introduced, as well. After each iteration the magnitude characteristic of the resulting filter is determined by using the non-uniform DFT and compared with the required one; if the errors are larger than the acceptable levels (set by the user) a new iteration is run; the length of the resulting filter and the values of its coefficients are also taken into consideration when deciding a re-run. To demonstrate the efficiency of the proposed method a tool for designing FIR filters that match human audiograms was implemented in LabVIEW. It was shown that the resulting filters have smaller coefficients than the standard one, and can also have lower order, while the errors remain relatively small.
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 Synthesis Tool Based on Genetic Algorithm for FIR Filters with User-Defined Magnitude Characteristics, Szopos, Ervin, Neag, Marius, Saracut, Ioana, Popescu, Victor, Topa, Marina, Circuits, Systems, and Signal Processing, ISSN 0278-081X, Issue 1, Volume 35, 2016.
Digital Object Identifier: 10.1007/s00034-015-0054-0 [CrossRef]
 Modelling Audiograms for People with Dementia Who Experience Hearing Loss Using Multiple Linear Regression Method, Elkhouly, Abeer, Rahim, Hasliza A, Abdulaziz, Nidhal, Abd Malek, Mohamed Fareq, 2020 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI), ISBN 978-1-7281-7315-3, 2020.
Digital Object Identifier: 10.1109/CCCI49893.2020.9256679 [CrossRef]
 IIR filter synthesis based on Real-Coded Genetic Algorithm for human audiogram emulation, Szopos, Ervin, Saracut, Ioana, Farcas, Calin, Neag, Marius, Topa, Marina, 2015 International Symposium on Signals, Circuits and Systems (ISSCS), ISBN 978-1-4673-7488-0, 2015.
Digital Object Identifier: 10.1109/ISSCS.2015.7203955 [CrossRef]
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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