matlab toolbox dependencies Search Results


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MathWorks Inc data acquisition daq toolbox
Analog input recordings <t>with</t> <t>MATLAB</t> <t>DAQ</t> Toolbox and NIMH DAQ Toolbox. The input signal was a 20-Hz sine wave and the sampling rate was 1 kHz. A. Due to the delay in sample transfers, MATLAB DAQ can check new samples only at a rate of ~67 Hz during the logging-mode recordings, which results in aliasing (see the main text). The buffer size was adjusted so that the sample transfers could occur as frequently as possible. B. NIMH DAQ Toolbox retrieves new samples at any time requested even in the logging mode and shows no aliasing. C. The number of available samples increases by 1 every millisecond in NIMH DAQ Toolbox, whereas it increases by 15 every 15 milliseconds in MATLAB DAQ Toolbox. D. The temporal cost of checking the current input state as a function of the number of channels.
Data Acquisition Daq 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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MathWorks Inc dependencies matlab r2015a
Analog input recordings <t>with</t> <t>MATLAB</t> <t>DAQ</t> Toolbox and NIMH DAQ Toolbox. The input signal was a 20-Hz sine wave and the sampling rate was 1 kHz. A. Due to the delay in sample transfers, MATLAB DAQ can check new samples only at a rate of ~67 Hz during the logging-mode recordings, which results in aliasing (see the main text). The buffer size was adjusted so that the sample transfers could occur as frequently as possible. B. NIMH DAQ Toolbox retrieves new samples at any time requested even in the logging mode and shows no aliasing. C. The number of available samples increases by 1 every millisecond in NIMH DAQ Toolbox, whereas it increases by 15 every 15 milliseconds in MATLAB DAQ Toolbox. D. The temporal cost of checking the current input state as a function of the number of channels.
Dependencies Matlab R2015a, 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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MathWorks Inc image processing toolboxtm
Analog input recordings <t>with</t> <t>MATLAB</t> <t>DAQ</t> Toolbox and NIMH DAQ Toolbox. The input signal was a 20-Hz sine wave and the sampling rate was 1 kHz. A. Due to the delay in sample transfers, MATLAB DAQ can check new samples only at a rate of ~67 Hz during the logging-mode recordings, which results in aliasing (see the main text). The buffer size was adjusted so that the sample transfers could occur as frequently as possible. B. NIMH DAQ Toolbox retrieves new samples at any time requested even in the logging mode and shows no aliasing. C. The number of available samples increases by 1 every millisecond in NIMH DAQ Toolbox, whereas it increases by 15 every 15 milliseconds in MATLAB DAQ Toolbox. D. The temporal cost of checking the current input state as a function of the number of channels.
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MathWorks Inc 2014b
Processing features of fully automated toolboxes
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Analog input recordings with MATLAB DAQ Toolbox and NIMH DAQ Toolbox. The input signal was a 20-Hz sine wave and the sampling rate was 1 kHz. A. Due to the delay in sample transfers, MATLAB DAQ can check new samples only at a rate of ~67 Hz during the logging-mode recordings, which results in aliasing (see the main text). The buffer size was adjusted so that the sample transfers could occur as frequently as possible. B. NIMH DAQ Toolbox retrieves new samples at any time requested even in the logging mode and shows no aliasing. C. The number of available samples increases by 1 every millisecond in NIMH DAQ Toolbox, whereas it increases by 15 every 15 milliseconds in MATLAB DAQ Toolbox. D. The temporal cost of checking the current input state as a function of the number of channels.

Journal: Journal of neuroscience methods

Article Title: NIMH MonkeyLogic: Behavioral control and data acquisition in MATLAB

doi: 10.1016/j.jneumeth.2019.05.002

Figure Lengend Snippet: Analog input recordings with MATLAB DAQ Toolbox and NIMH DAQ Toolbox. The input signal was a 20-Hz sine wave and the sampling rate was 1 kHz. A. Due to the delay in sample transfers, MATLAB DAQ can check new samples only at a rate of ~67 Hz during the logging-mode recordings, which results in aliasing (see the main text). The buffer size was adjusted so that the sample transfers could occur as frequently as possible. B. NIMH DAQ Toolbox retrieves new samples at any time requested even in the logging mode and shows no aliasing. C. The number of available samples increases by 1 every millisecond in NIMH DAQ Toolbox, whereas it increases by 15 every 15 milliseconds in MATLAB DAQ Toolbox. D. The temporal cost of checking the current input state as a function of the number of channels.

Article Snippet: It also depends on the legacy 32-bit interface of the MATLAB Data Acquisition (DAQ) Toolbox, which was discontinued from MATLAB R2016a.

Techniques: Sampling

Processing features of fully automated toolboxes

Journal: Human Brain Mapping

Article Title: A comparison of automated lesion segmentation approaches for chronic stroke T1‐weighted MRI data

doi: 10.1002/hbm.24729

Figure Lengend Snippet: Processing features of fully automated toolboxes

Article Snippet: Platform dependencies , MATLAB, SPM5+ , MATLAB 2014b+ (requires statistics and machine learning toolbox), SPM12+ , R v.3.0+, ANTsR package.

Techniques: