  In this study, we introduce a novel variant and application of the
Collaborative Representation based Classification in spectral domain for
recognition of the hand gestures using the raw surface Electromyography
signals. The intuitive use of spectral features are explained via circulant
matrices. The proposed Spectral Collaborative Representation based
Classification (SCRC) is able to recognize gestures with higher levels of
accuracy for a fairly rich gesture set. The worst recognition result which is
the best in the literature is obtained as 97.3\% among the four sets of the
experiments for each hand gestures. The recognition results are reported with a
substantial number of experiments and labeling computation.
