Title :
Hidden component analysis of undetermined recordings
Author_Institution :
Singapore Inst. of Manuf. Technol., Singapore
Abstract :
The aim of the study is to recover and detect the neglected hidden mirror neurons in the neuronal spikes recordings. The investigation and the detection of the hidden neurons were conducted using the standard and ensemble and complex Empirical Mode Decomposition (EMD). The extension to the field of complex numbers C is particularly important for the analysis of phase-dependent neuronal study. This allows us to combine the data driven nature of EMD with the power of complex algebra to model amplitude-phase relationships of the neurons. The analysis shows that the extensions of EMD to the recordings are magnificent. Simulations on trains of spiking neurons support the analysis.
Keywords :
algebra; neurophysiology; complex algebra; empirical mode decomposition; hidden component analysis; neglected hidden mirror neurons; phase-dependent neuronal study; undetermined recordings; Algebra; Analytical models; Brain modeling; Fault location; Manufacturing; Mirrors; Mouth; Neurons; Shape; Tongue; adaptive nonlinear estimation; hidden component analysis; noisy signals; unsupervised extraction;
Conference_Titel :
Industrial Electronics and Applications, 2008. ICIEA 2008. 3rd IEEE Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-1717-9
Electronic_ISBN :
978-1-4244-1718-6
DOI :
10.1109/ICIEA.2008.4582667