MnM

MnM is a set of Max/MSP externals based on FTM providing a unified framework for various techniques of classification, recognition and mapping for motion capture data, sound and music.

Features

• Hidden Markov Models
• Principal Components Analysis
• Singular Value Decomposition, LU and QR decompositions
• Non-negative Matrix Factorization and sparse decomposition
• multi-dimensionnal M to N mapping based on examples
• Multi-dimensioannal autocorrelation
• Matrix/Vector Statistics (min, max, mean, std, histogram, mahalanobis distance)

Publications

download PDF of NIME 2005 paper on MnM

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The MnM object set is released within the FTM distribution..