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Full-Text Articles in Signal Processing
Quantized Nonnegative Matrix Factorization, Ruairí De Fréin
Quantized Nonnegative Matrix Factorization, Ruairí De Fréin
Conference papers
Even though Nonnegative Matrix Factorization (NMF) in its original form performs rank reduction and signal compaction implicitly, it does not explicitly consider storage or transmission constraints. We propose a Frobenius-norm Quantized Nonnegative Matrix Factorization algorithm that is 1) almost as precise as traditional NMF for decomposition ranks of interest (with in 1-4dB), 2) admits to practical encoding techniques by learning a factorization which is simpler than NMF’s (by a factor of 20-70) and 3) exhibits a complexity which is comparable with state-of-the-art NMF methods. These properties are achieved by considering the quantization residual via an outer quantization optimization step, in …
A Graph-Based Approach To Symbolic Functional Decomposition Of Finite State Machines, Piotr Szotkowski, Mariusz Rawski, Henry Selvaraj
A Graph-Based Approach To Symbolic Functional Decomposition Of Finite State Machines, Piotr Szotkowski, Mariusz Rawski, Henry Selvaraj
Electrical & Computer Engineering Faculty Research
This paper discusses the symbolic functional decomposition method for implementing finite state machines in field-programmable gate array devices. This method is a viable alternative to the presently widespread two-step approaches to the problem, which consist of separate encoding and mapping stages; the proposed method does not have a separate decomposition step instead, the state's final encoding is introduced gradually on every decomposition iteration. Along with general description of the functional symbolic decomposition method's steps, the paper discusses various algorithms implementing the method and presents an example realisation of the most interesting algorithm. In the end, the paper compares the results …