matlab-based implementation Search Results


amigo toolbox  (MathWorks Inc)
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matlab 2024a version  (MathWorks Inc)
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open source customisable matlab based analysis toolbox  (MathWorks Inc)
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matlab toolbox dotcvp  (MathWorks Inc)
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Matlab Toolbox Dotcvp, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 97/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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simscape language  (MathWorks Inc)
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hartmann 1997 wide filter bands  (MathWorks Inc)
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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
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simulink based test modules  (MathWorks Inc)
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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.
Simulink Based Test Modules, 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
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calibration toolbox  (MathWorks Inc)
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MathWorks Inc calibration toolbox
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.
Calibration Toolbox, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 94/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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text-based simulation environment comsol script  (COMSOL Inc)
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COMSOL Inc text-based simulation environment comsol script
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.
Text Based Simulation Environment Comsol Script, supplied by COMSOL Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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model based design module  (MathWorks Inc)
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MathWorks Inc model based design module
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.
Model Based Design Module, 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
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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: