matlab rule-based functions Search Results


matlab rule-based functions  (MathWorks Inc)
90
MathWorks Inc matlab rule-based functions
Matlab Rule Based 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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trapezoidal rule-based matlab function trapz.m  (MathWorks Inc)
90
MathWorks Inc trapezoidal rule-based matlab function trapz.m
Trapezoidal Rule Based Matlab Function Trapz.M, 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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fuzzy rule-based classifier by rgrc  (MathWorks Inc)
90
MathWorks Inc fuzzy rule-based classifier by rgrc
The trained fuzzy classifiers in MATLAB by (a) clustering or (b) metaheuristics. (a) FCM. (b) Fuzzy classifier by <t>RGRC.</t>
Fuzzy Rule Based Classifier By Rgrc, 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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optpbn  (MathWorks Inc)
90
MathWorks Inc optpbn
A preliminary model structure is required as an input for the generation of <t>a</t> <t>PBN</t> model. The generated PBN models from different experimental conditions together with the corresponding measurement data are subsequently combined to generate an integrated optimisation problem which can be solved by various optimisation algorithms. Once the optimisation algorithm(s) generate sufficient amount of good parameter sets, a statistical analysis of the optimised parameter sets (i.e., of PBN's selection probabilities) is performed to indicate the identifiability and the sensitivity of parameters through the consideration on parameters' distribution. The <t>optPBN</t> scripts used for each task are given in parentheses.
Optpbn, 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/simulink  (MathWorks Inc)
90
MathWorks Inc matlab/simulink
A preliminary model structure is required as an input for the generation of <t>a</t> <t>PBN</t> model. The generated PBN models from different experimental conditions together with the corresponding measurement data are subsequently combined to generate an integrated optimisation problem which can be solved by various optimisation algorithms. Once the optimisation algorithm(s) generate sufficient amount of good parameter sets, a statistical analysis of the optimised parameter sets (i.e., of PBN's selection probabilities) is performed to indicate the identifiability and the sensitivity of parameters through the consideration on parameters' distribution. The <t>optPBN</t> scripts used for each task are given in parentheses.
Matlab/Simulink, 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 optimization toolbox  (MathWorks Inc)
90
MathWorks Inc matlab optimization toolbox
A preliminary model structure is required as an input for the generation of <t>a</t> <t>PBN</t> model. The generated PBN models from different experimental conditions together with the corresponding measurement data are subsequently combined to generate an integrated optimisation problem which can be solved by various optimisation algorithms. Once the optimisation algorithm(s) generate sufficient amount of good parameter sets, a statistical analysis of the optimised parameter sets (i.e., of PBN's selection probabilities) is performed to indicate the identifiability and the sensitivity of parameters through the consideration on parameters' distribution. The <t>optPBN</t> scripts used for each task are given in parentheses.
Matlab Optimization Toolbox, 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 fuzzy tool  (MathWorks Inc)
90
MathWorks Inc matlab fuzzy tool
A preliminary model structure is required as an input for the generation of <t>a</t> <t>PBN</t> model. The generated PBN models from different experimental conditions together with the corresponding measurement data are subsequently combined to generate an integrated optimisation problem which can be solved by various optimisation algorithms. Once the optimisation algorithm(s) generate sufficient amount of good parameter sets, a statistical analysis of the optimised parameter sets (i.e., of PBN's selection probabilities) is performed to indicate the identifiability and the sensitivity of parameters through the consideration on parameters' distribution. The <t>optPBN</t> scripts used for each task are given in parentheses.
Matlab Fuzzy Tool, 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 fuzzy toolbox  (MathWorks Inc)
90
MathWorks Inc matlab fuzzy toolbox
A preliminary model structure is required as an input for the generation of <t>a</t> <t>PBN</t> model. The generated PBN models from different experimental conditions together with the corresponding measurement data are subsequently combined to generate an integrated optimisation problem which can be solved by various optimisation algorithms. Once the optimisation algorithm(s) generate sufficient amount of good parameter sets, a statistical analysis of the optimised parameter sets (i.e., of PBN's selection probabilities) is performed to indicate the identifiability and the sensitivity of parameters through the consideration on parameters' distribution. The <t>optPBN</t> scripts used for each task are given in parentheses.
Matlab Fuzzy Toolbox, 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 fis editor  (MathWorks Inc)
90
MathWorks Inc matlab fis editor
A preliminary model structure is required as an input for the generation of <t>a</t> <t>PBN</t> model. The generated PBN models from different experimental conditions together with the corresponding measurement data are subsequently combined to generate an integrated optimisation problem which can be solved by various optimisation algorithms. Once the optimisation algorithm(s) generate sufficient amount of good parameter sets, a statistical analysis of the optimised parameter sets (i.e., of PBN's selection probabilities) is performed to indicate the identifiability and the sensitivity of parameters through the consideration on parameters' distribution. The <t>optPBN</t> scripts used for each task are given in parentheses.
Matlab Fis Editor, 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 kruskalwallis  (MathWorks Inc)
90
MathWorks Inc matlab function kruskalwallis
A preliminary model structure is required as an input for the generation of <t>a</t> <t>PBN</t> model. The generated PBN models from different experimental conditions together with the corresponding measurement data are subsequently combined to generate an integrated optimisation problem which can be solved by various optimisation algorithms. Once the optimisation algorithm(s) generate sufficient amount of good parameter sets, a statistical analysis of the optimised parameter sets (i.e., of PBN's selection probabilities) is performed to indicate the identifiability and the sensitivity of parameters through the consideration on parameters' distribution. The <t>optPBN</t> scripts used for each task are given in parentheses.
Matlab Function Kruskalwallis, 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 fit.m  (MathWorks Inc)
90
MathWorks Inc matlab function fit.m
A preliminary model structure is required as an input for the generation of <t>a</t> <t>PBN</t> model. The generated PBN models from different experimental conditions together with the corresponding measurement data are subsequently combined to generate an integrated optimisation problem which can be solved by various optimisation algorithms. Once the optimisation algorithm(s) generate sufficient amount of good parameter sets, a statistical analysis of the optimised parameter sets (i.e., of PBN's selection probabilities) is performed to indicate the identifiability and the sensitivity of parameters through the consideration on parameters' distribution. The <t>optPBN</t> scripts used for each task are given in parentheses.
Matlab Function Fit.M, 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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fmincon function  (MathWorks Inc)
90
MathWorks Inc fmincon function
A preliminary model structure is required as an input for the generation of <t>a</t> <t>PBN</t> model. The generated PBN models from different experimental conditions together with the corresponding measurement data are subsequently combined to generate an integrated optimisation problem which can be solved by various optimisation algorithms. Once the optimisation algorithm(s) generate sufficient amount of good parameter sets, a statistical analysis of the optimised parameter sets (i.e., of PBN's selection probabilities) is performed to indicate the identifiability and the sensitivity of parameters through the consideration on parameters' distribution. The <t>optPBN</t> scripts used for each task are given in parentheses.
Fmincon 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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Image Search Results


The trained fuzzy classifiers in MATLAB by (a) clustering or (b) metaheuristics. (a) FCM. (b) Fuzzy classifier by RGRC.

Journal: Computational Intelligence and Neuroscience

Article Title: A Fuzzy Shell for Developing an Interpretable BCI Based on the Spatiotemporal Dynamics of the Evoked Oscillations

doi: 10.1155/2021/6685672

Figure Lengend Snippet: The trained fuzzy classifiers in MATLAB by (a) clustering or (b) metaheuristics. (a) FCM. (b) Fuzzy classifier by RGRC.

Article Snippet: We developed in MATLAB the fuzzy rule-based classifier by RGRC (described in ) and used membership functions in [ ].

Techniques:

A preliminary model structure is required as an input for the generation of a PBN model. The generated PBN models from different experimental conditions together with the corresponding measurement data are subsequently combined to generate an integrated optimisation problem which can be solved by various optimisation algorithms. Once the optimisation algorithm(s) generate sufficient amount of good parameter sets, a statistical analysis of the optimised parameter sets (i.e., of PBN's selection probabilities) is performed to indicate the identifiability and the sensitivity of parameters through the consideration on parameters' distribution. The optPBN scripts used for each task are given in parentheses.

Journal: PLoS ONE

Article Title: optPBN: An Optimisation Toolbox for Probabilistic Boolean Networks

doi: 10.1371/journal.pone.0098001

Figure Lengend Snippet: A preliminary model structure is required as an input for the generation of a PBN model. The generated PBN models from different experimental conditions together with the corresponding measurement data are subsequently combined to generate an integrated optimisation problem which can be solved by various optimisation algorithms. Once the optimisation algorithm(s) generate sufficient amount of good parameter sets, a statistical analysis of the optimised parameter sets (i.e., of PBN's selection probabilities) is performed to indicate the identifiability and the sensitivity of parameters through the consideration on parameters' distribution. The optPBN scripts used for each task are given in parentheses.

Article Snippet: Based on the existing functionalities of the BN/PBN toolbox , we introduce optPBN , a Matlab-based optimisation toolbox for probabilistic Boolean networks. optPBN allows for a simple generation of PBN models from rule-based Boolean modelling.

Techniques: Generated, Selection