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InfoMax Inc fastica
Fastica, supplied by InfoMax 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/product/fastica/fastica/pm38838840-297-24-29
Average 90 stars, based on 1 article reviews

fastica - by Bioz Stars, 2026-11

90/100 stars

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Article Title: Independent component analysis based algorithms for high-density electromyogram decomposition: Experimental evaluation of upper extremity muscles.
Article Snippet: Independent component analysis based algorithms for high-density electromyogram decomposition: Experimental evaluation of upper extremity muscles

Article Title: Non-Adaptive Methods for Fetal ECG Signal Processing: A Review and Appraisal
Article Snippet: Marossero et al. [ ] used a MeRMaId algorithm to compare FastICA and InfoMax.

Article Title: Expanding the clinical application of OPM-MEG using an effective automatic suppression method for the dental brace metal artifact.
Article Snippet: Artifact suppression methods Subject 1 Subject 3 Subject 4 Average values SNR (dB) SNR (dB) SNR (dB) SNR (dB) unprocessed 8.40 10.33 9.88 9.54 FastICA 9.49 12.01 10.08 10.53 Infomax 9.60 13.50 10.55 11.22 AMUSE 8.26 10.33 12.13 10.24 Proposed Method 10.46 14.17 11.36 12.00 metal artifacts were significantly influenced by respiration and motion modulation (Fig. 2).

Article Title: Dynamics of task-related electrophysiological networks: a benchmarking study.
Article Snippet: All significant components extracted from the ve ICA methods (JADE, InfoMax, FastICA, CoM2 and PSAUD), NMF nd Kmeans methods were categorized as ‘Mot’ network due to the trong participation of sensorimotor nodes in these networks (sensori- otor strength ratio > 0.6) although some of them may involve addiional few connections to other regions.

Imaging:

Article Title: Independent component analysis of hydrodynamic bubbles’ properties
Article Snippet: .. Neural Networks2017–May 2486–93 Chernomyrdin N V., Zaytsev K I, Lesnichaya A D, Kudrin K G, Cherkasova O P, Kurlov V N, Shikunova I A, Perchik A V., Yurchenko S O and Reshetov I V. 2016 Principle component analysis and linear discriminant analysis of multi-spectral autofluorescence imaging data for differentiating basal cell carcinoma and healthy skin 99760B Heaton C and Ripley B D 2017 Package ‘ fastICA ’ Langlois D, Chartier S and Gosselin D 2010 An Introduction to Independent Component Analysis: InfoMax and FastICA algorithms Tutor. ..

Activity Assay:

Article Title: Blind Nonnegative Source Separation Using Biological Neural Networks.
Article Snippet: .. For Figures 3 to 6 the following parameters were found to be best performing as a result of our grid search: fastICA NPCA NSM (activity) NSM (time) d = 3 (10, 0.01) (10, 0.1) (10, 0.8) (10, 0.1) d = 5 (100, 0.01) (10, 0.01) (10, 0.9) (10, 0.01) d = 7 (100, 0.01) (100, 0.01) (10, 0.9) (10, 0.1) d = 10 (100, 0.01) (1000, 0.01) (10, 0.9) (10, 0.01) Images (104, 0.01) (1000, 0.01) (100, 0.9) NA Two-Layer Offline Infomax ICA Linsker’s Algorithm d = 3 (100, 1, 10, 0.8) (106, 0.001) (1000, 0.2) (1000, 0.2) d = 5 (100, 1, 10, 0.9) (106, 0.001) (1000, 0.2) (1000, 0.2) d = 7 (100, 1, 10, 0.9) (106, 0.01) (1000, 0.2) (1000, 0.2) d = 10 (100, 1, 10, 0.9) (106, 0.01) (1000, 0.2) (1000, 0.2) Images (100, 1, 100, 0.9) NA NA NA U nc or re ct ed Pr oo f ..