matlab-based filtering Search Results


98
MathWorks Inc signal processing toolbox uses window based filtering
Signal Processing Toolbox Uses Window Based Filtering, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 98/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/signal processing toolbox uses window based filtering/product/MathWorks Inc
Average 98 stars, based on 1 article reviews
signal processing toolbox uses window based filtering - by Bioz Stars, 2026-05
98/100 stars
  Buy from Supplier

95
MathWorks Inc hartmann 1997 wide filter bands
FIG. 2. Spectra of the low-frequency [(A), (B), (D), and (F)] and high-frequency [(C), (E), and (G)] filtered noises, with (A)–(C) indicating the spectra when there was no <t>gammatone</t> filtering (0-dB level change), (D) and (E) when the random-level change was 10 dB (10-dB level change), and (F) and (G) when the random-level change was 20 dB (20-dB level change). The spectrum shown in (A) is for a 200-ms filtered noise, and in all other panels [(B)–(G)], the duration was 2500 ms. The spectra are only examples, as the spectra varied randomly due to the random variation in the level of each gammatone filter. In each case, the amplitudes shown in the figure are scaled to that of the maximum amplitude for the particular noise sample.
Hartmann 1997 Wide Filter Bands, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 95/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/hartmann 1997 wide filter bands/product/MathWorks Inc
Average 95 stars, based on 1 article reviews
hartmann 1997 wide filter bands - by Bioz Stars, 2026-05
95/100 stars
  Buy from Supplier

96
MathWorks Inc wavelet filtering
FIG. 2. Spectra of the low-frequency [(A), (B), (D), and (F)] and high-frequency [(C), (E), and (G)] filtered noises, with (A)–(C) indicating the spectra when there was no <t>gammatone</t> filtering (0-dB level change), (D) and (E) when the random-level change was 10 dB (10-dB level change), and (F) and (G) when the random-level change was 20 dB (20-dB level change). The spectrum shown in (A) is for a 200-ms filtered noise, and in all other panels [(B)–(G)], the duration was 2500 ms. The spectra are only examples, as the spectra varied randomly due to the random variation in the level of each gammatone filter. In each case, the amplitudes shown in the figure are scaled to that of the maximum amplitude for the particular noise sample.
Wavelet Filtering, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/wavelet filtering/product/MathWorks Inc
Average 96 stars, based on 1 article reviews
wavelet filtering - by Bioz Stars, 2026-05
96/100 stars
  Buy from Supplier

Image Search Results


FIG. 2. Spectra of the low-frequency [(A), (B), (D), and (F)] and high-frequency [(C), (E), and (G)] filtered noises, with (A)–(C) indicating the spectra when there was no gammatone filtering (0-dB level change), (D) and (E) when the random-level change was 10 dB (10-dB level change), and (F) and (G) when the random-level change was 20 dB (20-dB level change). The spectrum shown in (A) is for a 200-ms filtered noise, and in all other panels [(B)–(G)], the duration was 2500 ms. The spectra are only examples, as the spectra varied randomly due to the random variation in the level of each gammatone filter. In each case, the amplitudes shown in the figure are scaled to that of the maximum amplitude for the particular noise sample.

Journal: The Journal of the Acoustical Society of America

Article Title: Randomizing spectral cues used to resolve front-back reversals in sound-source localization.

doi: 10.1121/10.0020563

Figure Lengend Snippet: FIG. 2. Spectra of the low-frequency [(A), (B), (D), and (F)] and high-frequency [(C), (E), and (G)] filtered noises, with (A)–(C) indicating the spectra when there was no gammatone filtering (0-dB level change), (D) and (E) when the random-level change was 10 dB (10-dB level change), and (F) and (G) when the random-level change was 20 dB (20-dB level change). The spectrum shown in (A) is for a 200-ms filtered noise, and in all other panels [(B)–(G)], the duration was 2500 ms. The spectra are only examples, as the spectra varied randomly due to the random variation in the level of each gammatone filter. In each case, the amplitudes shown in the figure are scaled to that of the maximum amplitude for the particular noise sample.

Article Snippet: In all other cases, the spectrum of each noise was divided into a series of successive, non-overlapping 1-Cam [equivalent rectangular bandwidth (ERB); see Moore and Glasberg (1983) and Hartmann (1997)] wide filter bands (based on implementation of a gammatone filter bank in MATLAB’s Audio Toolbox).

Techniques: