matlab fft routine Search Results


fast fourier transform (fft) matlab routine  (MathWorks Inc)
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Fast Fourier Transform (Fft) Matlab Routine, 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 fft routine  (MathWorks Inc)
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Matlab Fft Routine, 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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2d-fft routine  (MathWorks Inc)
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2d Fft Routine, 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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fft routine  (MathWorks Inc)
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Fft Routine, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 93/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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discrete fourier transform matlab fft routine  (MathWorks Inc)
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Discrete Fourier Transform Matlab Fft Routine, 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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fast fourier transform (fft) routines  (MathWorks Inc)
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MathWorks Inc fast fourier transform (fft) routines
Fast Fourier Transform (Fft) Routines, 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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embedded fft function  (MathWorks Inc)
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MathWorks Inc embedded fft function
Spectral analysis of sleep electroencephalography during sleep fragmentation (SF) and recovery. (A,B) Frequency spectrum of slow wave <t>sleep</t> <t>(SWS)</t> during dark (upper panel) and light phase (lower panel) of the SF protocol. Power is expressed in percent of baseline for each individual and averaged (n for quiet control [QC] = 6, motor control [MC] = 8, fragmented [F] = 7). Horizontal gray bars indicate significant difference (P < 0.05 on Tukey post-significant one-way analysis of variance). Note the consistent increase in power in theta to gamma bands (4–40 Hz). (C) Note normalization of theta-gamma effect during the dark phase on R1 but significant increase in slow wave activity (SWA; insert). (D–I) Dynamics of the power changes at transitions from wake (W) to SWS (t = 0) and from paradoxical sleep (PS) to SWS (t = 0) during light phase of D1 (n for QC = 6, MC = 8, F = 7), D14 (n = 6 per group) and R1 (n = 6 per group). Power is expressed in percent of SWS values during normalizing day. 1 Hz <t>FFT</t> values (displayed in A–C) were summed up in classic frequency bands, α and β were grouped. Horizontal gray bars indicate significant difference between F compared to both MC and QC (Tukey possignificant one-way analysis of variance, P < 0.05 for both). Note the overshoot of theta to gamma frequencies in the F group following SWS onset during SF (D,E) and its disappearance on R1 (F). Note also the increase in SWA buildup rate on D14 (E). Note that α and β power transitory increase before PS onset is slightly delayed in F group (G,H).
Embedded Fft 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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standard fft routines  (MathWorks Inc)
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MathWorks Inc standard fft routines
Spectral analysis of sleep electroencephalography during sleep fragmentation (SF) and recovery. (A,B) Frequency spectrum of slow wave <t>sleep</t> <t>(SWS)</t> during dark (upper panel) and light phase (lower panel) of the SF protocol. Power is expressed in percent of baseline for each individual and averaged (n for quiet control [QC] = 6, motor control [MC] = 8, fragmented [F] = 7). Horizontal gray bars indicate significant difference (P < 0.05 on Tukey post-significant one-way analysis of variance). Note the consistent increase in power in theta to gamma bands (4–40 Hz). (C) Note normalization of theta-gamma effect during the dark phase on R1 but significant increase in slow wave activity (SWA; insert). (D–I) Dynamics of the power changes at transitions from wake (W) to SWS (t = 0) and from paradoxical sleep (PS) to SWS (t = 0) during light phase of D1 (n for QC = 6, MC = 8, F = 7), D14 (n = 6 per group) and R1 (n = 6 per group). Power is expressed in percent of SWS values during normalizing day. 1 Hz <t>FFT</t> values (displayed in A–C) were summed up in classic frequency bands, α and β were grouped. Horizontal gray bars indicate significant difference between F compared to both MC and QC (Tukey possignificant one-way analysis of variance, P < 0.05 for both). Note the overshoot of theta to gamma frequencies in the F group following SWS onset during SF (D,E) and its disappearance on R1 (F). Note also the increase in SWA buildup rate on D14 (E). Note that α and β power transitory increase before PS onset is slightly delayed in F group (G,H).
Standard Fft Routines, 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
https://www.bioz.com/result/standard fft routines/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
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Image Search Results


Spectral analysis of sleep electroencephalography during sleep fragmentation (SF) and recovery. (A,B) Frequency spectrum of slow wave sleep (SWS) during dark (upper panel) and light phase (lower panel) of the SF protocol. Power is expressed in percent of baseline for each individual and averaged (n for quiet control [QC] = 6, motor control [MC] = 8, fragmented [F] = 7). Horizontal gray bars indicate significant difference (P < 0.05 on Tukey post-significant one-way analysis of variance). Note the consistent increase in power in theta to gamma bands (4–40 Hz). (C) Note normalization of theta-gamma effect during the dark phase on R1 but significant increase in slow wave activity (SWA; insert). (D–I) Dynamics of the power changes at transitions from wake (W) to SWS (t = 0) and from paradoxical sleep (PS) to SWS (t = 0) during light phase of D1 (n for QC = 6, MC = 8, F = 7), D14 (n = 6 per group) and R1 (n = 6 per group). Power is expressed in percent of SWS values during normalizing day. 1 Hz FFT values (displayed in A–C) were summed up in classic frequency bands, α and β were grouped. Horizontal gray bars indicate significant difference between F compared to both MC and QC (Tukey possignificant one-way analysis of variance, P < 0.05 for both). Note the overshoot of theta to gamma frequencies in the F group following SWS onset during SF (D,E) and its disappearance on R1 (F). Note also the increase in SWA buildup rate on D14 (E). Note that α and β power transitory increase before PS onset is slightly delayed in F group (G,H).

Journal: Sleep

Article Title: Sustained Sleep Fragmentation Induces Sleep Homeostasis in Mice

doi: 10.5665/sleep.4572

Figure Lengend Snippet: Spectral analysis of sleep electroencephalography during sleep fragmentation (SF) and recovery. (A,B) Frequency spectrum of slow wave sleep (SWS) during dark (upper panel) and light phase (lower panel) of the SF protocol. Power is expressed in percent of baseline for each individual and averaged (n for quiet control [QC] = 6, motor control [MC] = 8, fragmented [F] = 7). Horizontal gray bars indicate significant difference (P < 0.05 on Tukey post-significant one-way analysis of variance). Note the consistent increase in power in theta to gamma bands (4–40 Hz). (C) Note normalization of theta-gamma effect during the dark phase on R1 but significant increase in slow wave activity (SWA; insert). (D–I) Dynamics of the power changes at transitions from wake (W) to SWS (t = 0) and from paradoxical sleep (PS) to SWS (t = 0) during light phase of D1 (n for QC = 6, MC = 8, F = 7), D14 (n = 6 per group) and R1 (n = 6 per group). Power is expressed in percent of SWS values during normalizing day. 1 Hz FFT values (displayed in A–C) were summed up in classic frequency bands, α and β were grouped. Horizontal gray bars indicate significant difference between F compared to both MC and QC (Tukey possignificant one-way analysis of variance, P < 0.05 for both). Note the overshoot of theta to gamma frequencies in the F group following SWS onset during SF (D,E) and its disappearance on R1 (F). Note also the increase in SWA buildup rate on D14 (E). Note that α and β power transitory increase before PS onset is slightly delayed in F group (G,H).

Article Snippet: Spectral Analysis After discarding epochs with lead motion artifacts, as well as one epoch preceding and one epoch following each state transition, EEG power spectra of remaining SWS epochs were calculated by a fast Fourier transform (FFT) using MATLAB embedded FFT function and personalized routines (Math-Works Inc., Natick, MA USA).

Techniques: Control, Activity Assay