Search Results for author: Ernest Fokoué

Found 8 papers, 2 papers with code

A Novel Use of Discrete Wavelet Transform Features in the Prediction of Epileptic Seizures from EEG Data

no code implementations31 Jan 2021 Cyrille Feudjio, Victoire Djimna Noyum, Younous Perieukeu Mofendjou, Rockefeller, Ernest Fokoué

This paper demonstrates the predictive superiority of discrete wavelet transform (DWT) over previously used methods of feature extraction in the diagnosis of epileptic seizures from EEG data.

EEG General Classification

Boosting the Predictive Accurary of Singer Identification Using Discrete Wavelet Transform For Feature Extraction

no code implementations31 Jan 2021 Victoire Djimna Noyum, Younous Perieukeu Mofenjou, Cyrille Feudjio, Alkan Göktug, Ernest Fokoué

We conclude that, for a dataset of 4 singers and 200 songs, the best identification system consists of the DWT (db4) feature extraction introduced in this work combined with a linear support vector machine for identification resulting in a mean accuracy of 83. 96%.

Singer Identification

Nonnegative Matrix Factorization with Toeplitz Penalty

no code implementations7 Dec 2020 Matthew Corsetti, Ernest Fokoué

We compare the facial recognition performance of our new Toeplitz Nonnegative Matrix Factorization (TNMF) algorithm to the performance of the Zellner Nonnegative Matrix Factorization (ZNMF) algorithm which makes use of data-dependent auxiliary constraints.

Nonnegative Matrix Factorization with Zellner Penalty

no code implementations7 Dec 2020 Matthew Corsetti, Ernest Fokoué

Nonnegative matrix factorization (NMF) is a relatively new unsupervised learning algorithm that decomposes a nonnegative data matrix into a parts-based, lower dimensional, linear representation of the data.

Recommendation Systems

What do Asian Religions Have in Common? An Unsupervised Text Analytics Exploration

1 code implementation20 Dec 2019 Preeti Sah, Ernest Fokoué

The main source of various religious teachings is their sacred texts which vary from religion to religion based on different factors like the geographical location or time of the birth of a particular religion.

Multi-Stage Fault Warning for Large Electric Grids Using Anomaly Detection and Machine Learning

no code implementations15 Mar 2019 Sanjeev Raja, Ernest Fokoué

The time series data are first mapped to highly discriminative features by applying dimensionality reduction based on temporal autocorrelation.

Anomaly Detection Classification +5

A Mathematical Formalization of Hierarchical Temporal Memory's Spatial Pooler

1 code implementation22 Jan 2016 James Mnatzaganian, Ernest Fokoué, Dhireesha Kudithipudi

Hierarchical temporal memory (HTM) is an emerging machine learning algorithm, with the potential to provide a means to perform predictions on spatiotemporal data.

Dimensionality Reduction

Prediction Error Reduction Function as a Variable Importance Score

no code implementations25 Jan 2015 Ernest Fokoué

This paper introduces and develops a novel variable importance score function in the context of ensemble learning and demonstrates its appeal both theoretically and empirically.

Ensemble Learning

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