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Nonnegative Matrix Factorization (NMF) has been widely used in computer vision and pattern recognition. It aims to find two nonnegative matrices whose product can well approximate the original matrix, which naturally leads to parts-based representation. In this paper, we propose a Two Dimensional Nonnegative Matrix Factorization (2DNMF), specifically for a sequence of matrices. In contrast to NMF...
Repetition detection is a fundamental issue for music thumbnailing and summarization. In this paper, we propose a new feature, called chroma histogram, which enables us to find out repetitive segments from popular songs accurately and quickly. The feature is robust to tempo variation, because sequential information is removed during the process. The low dimensional feature guarantees a very low computational...
Window operations which are computationally intensive and data intensive are frequently used in image compression, pattern recognition and digital signal processing. Reconfigurable hardware boards provide a convenient and flexible solution to speed up these algorithms. This paper studies the effect of loop unrolling on the area, clock speed and throughput based on a data schedule method to find the...
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