2d fft matlab function fft2 Search Results


2-dimensional fft  (MathWorks Inc)
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MathWorks Inc 2-dimensional fft
Background image power spectra, RF locations, and adaptation. A: the locations of RFs are indicated by 1° yellow circles (the average RF size) at their locations on the background image during fixation 1. Adaptation appears to have occurred in the RFs on the first fixation and been over into the second fixation. The red square indicates the aggregate RF area for all neurons studied. In addition to the RFs, we show white circles to indicate the corresponding upper visual field locations where stimuli would appear on the second fixation; these were included for the 2AFC behavioral task, and presumably, adaptation occurred at these sites as well. B, left: a 2-dimensional (2-D) <t>FFT</t> (MATLAB <t>fft2)</t> of the entire background image (blue border). The red boxes show the aggregate RF area on the background image and its 2-D FFT. In both the overall image and the aggregate RF area, low spatial frequencies were dominant. C: radially averaged power spectra are shown for three 1° background-image RF areas used in the contrast sensitivity task (cyc/deg, cycles/degree). We examined the power spectra of all background-image RF areas and found them to be similarly dominated by lower spatial frequencies.
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fft algorithm (fft2  (MathWorks Inc)
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MathWorks Inc fft algorithm (fft2
Background image power spectra, RF locations, and adaptation. A: the locations of RFs are indicated by 1° yellow circles (the average RF size) at their locations on the background image during fixation 1. Adaptation appears to have occurred in the RFs on the first fixation and been over into the second fixation. The red square indicates the aggregate RF area for all neurons studied. In addition to the RFs, we show white circles to indicate the corresponding upper visual field locations where stimuli would appear on the second fixation; these were included for the 2AFC behavioral task, and presumably, adaptation occurred at these sites as well. B, left: a 2-dimensional (2-D) <t>FFT</t> (MATLAB <t>fft2)</t> of the entire background image (blue border). The red boxes show the aggregate RF area on the background image and its 2-D FFT. In both the overall image and the aggregate RF area, low spatial frequencies were dominant. C: radially averaged power spectra are shown for three 1° background-image RF areas used in the contrast sensitivity task (cyc/deg, cycles/degree). We examined the power spectra of all background-image RF areas and found them to be similarly dominated by lower spatial frequencies.
Fft Algorithm (Fft2, supplied by MathWorks 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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2-d fft  (MathWorks Inc)
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MathWorks Inc 2-d fft
Background image power spectra, RF locations, and adaptation. A: the locations of RFs are indicated by 1° yellow circles (the average RF size) at their locations on the background image during fixation 1. Adaptation appears to have occurred in the RFs on the first fixation and been over into the second fixation. The red square indicates the aggregate RF area for all neurons studied. In addition to the RFs, we show white circles to indicate the corresponding upper visual field locations where stimuli would appear on the second fixation; these were included for the 2AFC behavioral task, and presumably, adaptation occurred at these sites as well. B, left: a 2-dimensional (2-D) <t>FFT</t> (MATLAB <t>fft2)</t> of the entire background image (blue border). The red boxes show the aggregate RF area on the background image and its 2-D FFT. In both the overall image and the aggregate RF area, low spatial frequencies were dominant. C: radially averaged power spectra are shown for three 1° background-image RF areas used in the contrast sensitivity task (cyc/deg, cycles/degree). We examined the power spectra of all background-image RF areas and found them to be similarly dominated by lower spatial frequencies.
2 D Fft, supplied by MathWorks 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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matlab software r2018b  (MathWorks Inc)
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Background image power spectra, RF locations, and adaptation. A: the locations of RFs are indicated by 1° yellow circles (the average RF size) at their locations on the background image during fixation 1. Adaptation appears to have occurred in the RFs on the first fixation and been over into the second fixation. The red square indicates the aggregate RF area for all neurons studied. In addition to the RFs, we show white circles to indicate the corresponding upper visual field locations where stimuli would appear on the second fixation; these were included for the 2AFC behavioral task, and presumably, adaptation occurred at these sites as well. B, left: a 2-dimensional (2-D) <t>FFT</t> (MATLAB <t>fft2)</t> of the entire background image (blue border). The red boxes show the aggregate RF area on the background image and its 2-D FFT. In both the overall image and the aggregate RF area, low spatial frequencies were dominant. C: radially averaged power spectra are shown for three 1° background-image RF areas used in the contrast sensitivity task (cyc/deg, cycles/degree). We examined the power spectra of all background-image RF areas and found them to be similarly dominated by lower spatial frequencies.
Matlab Software R2018b, supplied by MathWorks 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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2-d fft matlab function  (MathWorks Inc)
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MathWorks Inc 2-d fft matlab function
Background image power spectra, RF locations, and adaptation. A: the locations of RFs are indicated by 1° yellow circles (the average RF size) at their locations on the background image during fixation 1. Adaptation appears to have occurred in the RFs on the first fixation and been over into the second fixation. The red square indicates the aggregate RF area for all neurons studied. In addition to the RFs, we show white circles to indicate the corresponding upper visual field locations where stimuli would appear on the second fixation; these were included for the 2AFC behavioral task, and presumably, adaptation occurred at these sites as well. B, left: a 2-dimensional (2-D) <t>FFT</t> (MATLAB <t>fft2)</t> of the entire background image (blue border). The red boxes show the aggregate RF area on the background image and its 2-D FFT. In both the overall image and the aggregate RF area, low spatial frequencies were dominant. C: radially averaged power spectra are shown for three 1° background-image RF areas used in the contrast sensitivity task (cyc/deg, cycles/degree). We examined the power spectra of all background-image RF areas and found them to be similarly dominated by lower spatial frequencies.
2 D Fft Matlab Function, supplied by MathWorks 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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fft2 functions  (MathWorks Inc)
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MathWorks Inc fft2 functions
Background image power spectra, RF locations, and adaptation. A: the locations of RFs are indicated by 1° yellow circles (the average RF size) at their locations on the background image during fixation 1. Adaptation appears to have occurred in the RFs on the first fixation and been over into the second fixation. The red square indicates the aggregate RF area for all neurons studied. In addition to the RFs, we show white circles to indicate the corresponding upper visual field locations where stimuli would appear on the second fixation; these were included for the 2AFC behavioral task, and presumably, adaptation occurred at these sites as well. B, left: a 2-dimensional (2-D) <t>FFT</t> (MATLAB <t>fft2)</t> of the entire background image (blue border). The red boxes show the aggregate RF area on the background image and its 2-D FFT. In both the overall image and the aggregate RF area, low spatial frequencies were dominant. C: radially averaged power spectra are shown for three 1° background-image RF areas used in the contrast sensitivity task (cyc/deg, cycles/degree). We examined the power spectra of all background-image RF areas and found them to be similarly dominated by lower spatial frequencies.
Fft2 Functions, supplied by MathWorks 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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fft2( · ) function  (MathWorks Inc)
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MathWorks Inc fft2( · ) function
Computation time (a) for reconstruction of a final 2-D shear wave phase velocity map based on the LR and RL waves, for the original implementation of the LPVI method proposed in [22] (green and blue curves) and the modified, new approach proposed in this manuscript (red curve). Original 1 stands for adopting a built-in <t>fft2(·)</t> function in MATLAB whereas, Original 2 represents data for using dual fft(·) functions, respectively. Peak memory requirements, for all implementations, is marked as a dashed, square line in (b). Results are presented against number of DOFs corresponding to the number of pixels present in the spatial wavefield data (z and x). Calculations were performed on a standalone computer equipped with Windows 7 Professional operating system and the Intel(R) Xeon(R) CPU E5–2683 v4 @2.10 GHz processor. Padding factor of 1024 was used in the directions z and x, as well as, in the time domain.
Fft2( · ) Function, supplied by MathWorks 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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fft2 matlab function  (MathWorks Inc)
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MathWorks Inc fft2 matlab function
Computation time (a) for reconstruction of a final 2-D shear wave phase velocity map based on the LR and RL waves, for the original implementation of the LPVI method proposed in [22] (green and blue curves) and the modified, new approach proposed in this manuscript (red curve). Original 1 stands for adopting a built-in <t>fft2(·)</t> function in MATLAB whereas, Original 2 represents data for using dual fft(·) functions, respectively. Peak memory requirements, for all implementations, is marked as a dashed, square line in (b). Results are presented against number of DOFs corresponding to the number of pixels present in the spatial wavefield data (z and x). Calculations were performed on a standalone computer equipped with Windows 7 Professional operating system and the Intel(R) Xeon(R) CPU E5–2683 v4 @2.10 GHz processor. Padding factor of 1024 was used in the directions z and x, as well as, in the time domain.
Fft2 Matlab Function, supplied by MathWorks 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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matlab function fft2  (MathWorks Inc)
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MathWorks Inc matlab function fft2
Computation time (a) for reconstruction of a final 2-D shear wave phase velocity map based on the LR and RL waves, for the original implementation of the LPVI method proposed in [22] (green and blue curves) and the modified, new approach proposed in this manuscript (red curve). Original 1 stands for adopting a built-in <t>fft2(·)</t> function in MATLAB whereas, Original 2 represents data for using dual fft(·) functions, respectively. Peak memory requirements, for all implementations, is marked as a dashed, square line in (b). Results are presented against number of DOFs corresponding to the number of pixels present in the spatial wavefield data (z and x). Calculations were performed on a standalone computer equipped with Windows 7 Professional operating system and the Intel(R) Xeon(R) CPU E5–2683 v4 @2.10 GHz processor. Padding factor of 1024 was used in the directions z and x, as well as, in the time domain.
Matlab Function Fft2, supplied by MathWorks 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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fft2 (matlab)  (MathWorks Inc)
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MathWorks Inc fft2 (matlab)
Computation time (a) for reconstruction of a final 2-D shear wave phase velocity map based on the LR and RL waves, for the original implementation of the LPVI method proposed in [22] (green and blue curves) and the modified, new approach proposed in this manuscript (red curve). Original 1 stands for adopting a built-in <t>fft2(·)</t> function in MATLAB whereas, Original 2 represents data for using dual fft(·) functions, respectively. Peak memory requirements, for all implementations, is marked as a dashed, square line in (b). Results are presented against number of DOFs corresponding to the number of pixels present in the spatial wavefield data (z and x). Calculations were performed on a standalone computer equipped with Windows 7 Professional operating system and the Intel(R) Xeon(R) CPU E5–2683 v4 @2.10 GHz processor. Padding factor of 1024 was used in the directions z and x, as well as, in the time domain.
Fft2 (Matlab), supplied by MathWorks 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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Image Search Results


Background image power spectra, RF locations, and adaptation. A: the locations of RFs are indicated by 1° yellow circles (the average RF size) at their locations on the background image during fixation 1. Adaptation appears to have occurred in the RFs on the first fixation and been over into the second fixation. The red square indicates the aggregate RF area for all neurons studied. In addition to the RFs, we show white circles to indicate the corresponding upper visual field locations where stimuli would appear on the second fixation; these were included for the 2AFC behavioral task, and presumably, adaptation occurred at these sites as well. B, left: a 2-dimensional (2-D) FFT (MATLAB fft2) of the entire background image (blue border). The red boxes show the aggregate RF area on the background image and its 2-D FFT. In both the overall image and the aggregate RF area, low spatial frequencies were dominant. C: radially averaged power spectra are shown for three 1° background-image RF areas used in the contrast sensitivity task (cyc/deg, cycles/degree). We examined the power spectra of all background-image RF areas and found them to be similarly dominated by lower spatial frequencies.

Journal: Journal of Neurophysiology

Article Title: Contrast sensitivity, V1 neural activity, and natural vision

doi: 10.1152/jn.00635.2016

Figure Lengend Snippet: Background image power spectra, RF locations, and adaptation. A: the locations of RFs are indicated by 1° yellow circles (the average RF size) at their locations on the background image during fixation 1. Adaptation appears to have occurred in the RFs on the first fixation and been over into the second fixation. The red square indicates the aggregate RF area for all neurons studied. In addition to the RFs, we show white circles to indicate the corresponding upper visual field locations where stimuli would appear on the second fixation; these were included for the 2AFC behavioral task, and presumably, adaptation occurred at these sites as well. B, left: a 2-dimensional (2-D) FFT (MATLAB fft2) of the entire background image (blue border). The red boxes show the aggregate RF area on the background image and its 2-D FFT. In both the overall image and the aggregate RF area, low spatial frequencies were dominant. C: radially averaged power spectra are shown for three 1° background-image RF areas used in the contrast sensitivity task (cyc/deg, cycles/degree). We examined the power spectra of all background-image RF areas and found them to be similarly dominated by lower spatial frequencies.

Article Snippet: B , left : a 2-dimensional (2-D) FFT (MATLAB fft2) of the entire background image (blue border).

Techniques:

Computation time (a) for reconstruction of a final 2-D shear wave phase velocity map based on the LR and RL waves, for the original implementation of the LPVI method proposed in [22] (green and blue curves) and the modified, new approach proposed in this manuscript (red curve). Original 1 stands for adopting a built-in fft2(·) function in MATLAB whereas, Original 2 represents data for using dual fft(·) functions, respectively. Peak memory requirements, for all implementations, is marked as a dashed, square line in (b). Results are presented against number of DOFs corresponding to the number of pixels present in the spatial wavefield data (z and x). Calculations were performed on a standalone computer equipped with Windows 7 Professional operating system and the Intel(R) Xeon(R) CPU E5–2683 v4 @2.10 GHz processor. Padding factor of 1024 was used in the directions z and x, as well as, in the time domain.

Journal: IEEE transactions on ultrasonics, ferroelectrics, and frequency control

Article Title: Fast Local Phase Velocity Based Imaging (LPVI): Shear Wave Particle Velocity and Displacement Motion Study

doi: 10.1109/TUFFC.2019.2948512

Figure Lengend Snippet: Computation time (a) for reconstruction of a final 2-D shear wave phase velocity map based on the LR and RL waves, for the original implementation of the LPVI method proposed in [22] (green and blue curves) and the modified, new approach proposed in this manuscript (red curve). Original 1 stands for adopting a built-in fft2(·) function in MATLAB whereas, Original 2 represents data for using dual fft(·) functions, respectively. Peak memory requirements, for all implementations, is marked as a dashed, square line in (b). Results are presented against number of DOFs corresponding to the number of pixels present in the spatial wavefield data (z and x). Calculations were performed on a standalone computer equipped with Windows 7 Professional operating system and the Intel(R) Xeon(R) CPU E5–2683 v4 @2.10 GHz processor. Padding factor of 1024 was used in the directions z and x, as well as, in the time domain.

Article Snippet: Original 1 stands for adopting a built-in fft2( · ) function in MATLAB whereas, Original 2 represents data for using dual fft( · ) functions, respectively.

Techniques: Shear, Modification