Andere Kunden interessierten sich auch für
![Improved Unsaturated to Saturated Logic Level Translation]( "Improved Unsaturated to Saturated Logic Level Translation")
Improved Unsaturated to Saturated Logic Level Translation26,99 €![Improving reordering and modeling in statistical machine translation]( "Improving reordering and modeling in statistical machine translation")
Improving reordering and modeling in statistical machine translation51,99 €![SIGN LANGUAGE TO SPEECH TRANSLATION USING ARDUINO]( "SIGN LANGUAGE TO SPEECH TRANSLATION USING ARDUINO")
SIGN LANGUAGE TO SPEECH TRANSLATION USING ARDUINO29,99 €![Using Bayes and Image Morphology for Markerless Human Motion Capture]( "Using Bayes and Image Morphology for Markerless Human Motion Capture")
Using Bayes and Image Morphology for Markerless Human Motion Capture38,99 €![Statistical Methods in Sonar]( "Statistical Methods in Sonar")
Statistical Methods in Sonar42,99 €![Multi-Media Document Translation]( "Multi-Media Document Translation")
Multi-Media Document Translation132,99 €![Sources of High-Intensity Ultrasound]( "Sources of High-Intensity Ultrasound")
Sources of High-Intensity Ultrasound83,99 €
"Translation of Human Thoughts into Machine Motion": First Edition is basically a modified form of my research work on pattern recognition and classification of human thoughts. Electroencephalogram (EEG) is the language of human thoughts and here we are interested to detect and understand that language in order to drive a machine. Human brainwave is just like a signature, varies from person to person and also varies under different conditions. The works regarding brainwave study and signature detection on human subject have been done by my co-author, whereas the pattern recognition and classification parts have been done by me. A few statistical and Neural Network algorithms have been taken into account in order to classify EEG patterns recorded in different situations but from a single human subject, and the classification accuracy has reached a satisfactory level . Broadly, the aim is supposed to make successful Brain- Machine Interface and, therefore, EEG data from multiple subjects is needed for that task along with some modified classification algorithms. I believe I will be able to present you this approach too in the later editions of the book.