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In this work, we propose a novel convex combination algorithm incorporating two different-step-size adaptive filters derived from the logarithmic cost function. Recently, to incorporate the advantages of the different-order-norm-based cost functions without the need of a priori knowledge on signal statistics, the cost function using a logarithmic penalty was introduced. There are two different versions...
We propose an adaptive combination of a proportionate normalized least-mean-square with individual activation factors (IAF-PNLMS) and a normalized mean-square (NLMS) for the sparse system. The IAF-PNLMS has the fastest initial convergence rate among the algorithms for the sparse system. The NLMS has a low misalignment for various systems. To obtain both fast convergence rate and a low misalignment,...
It is well known that the cost of executing the sequential portion of a program will limit and sometimes even eclipse the gains brought by processing in parallel the rest of the program. This means that serious consideration should be brought to bear on accelerating the execution of this unavoidable sequential part. Such acceleration can be done by boosting the operating frequency in a symmetric multicore...
Utilization of a core with delay faults by frequency scaling reduces performance degradation in a multicore processor. When the frequency of a delay fault core is decreased, frequencies of the rest cores can be increased within a fixed power budget since the amount of dynamic power is proportional to the clock frequency. We propose two speedup models based on modified Amdahl's law for the frequency...
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