Abstract: Discrete wavelet transform (DWT) is sensitive to the translation/shift of input signals, so its effectiveness could be negatively impacted when it encounters translation among signals. This paper proposes a redundant DWT (RDWT) based signal registration and classification method that can solve DWT's translation sensitivity, fulfill signal classification when there are translation variances among signals, and simultaneously accomplish signal registration and translation invariant wavelet coefficient extraction. To the reference signal, we perform DWT on it. To the test signal, we perform RDWT, obtain the DWT result for its translation, and compute the similarity between the translated test signal and reference signals based on the DWT results. Then, we classify the test signal and determine its translation with respect to the reference signal according to the similarity criterion. Simulation results on the ECG signals prove the effectiveness of ourRDWT based method.