Incoherent Dictionary Pair Learning: Application to a Novel Open-Source Database of Chinese Numbers
Vahid Abolghasemi, Mingyang Chen, Ali Alameer, Saideh Ferdowsi, Jonathon A. Chambers, Kianoush Nazarpour · IEEE Signal Processing Letters · 2018
We enhance the efficacy of an existing dictionary pair learning algorithm by adding a dictionary incoherence penalty term. After presenting an alternating minimization solution, we apply the proposed incoherent dictionary pair learning (InDPL) method in classification of a novel open-source database of Chinese numbers. Benchmarking results confirm that the InDPL algorithm offers enhanced classification accuracy, especially when the number of training samples is limited.