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[19] T. Ushio and K. Hirai, " Chaotic behavior in piecewise-linear sampled data control systems, " Int. Snapback repellers as a cause of chaotic vibration of the wave equation with a van der Pol boundary condition and energy injection at the middle of the span, " Bollt, " Stability of order: An example of chaos " near " a linear map, " Int. Abstract—This(More)
Visual data comprise of multi-scale and inhomogeneous signals. In this paper, we exploit these characteristics and develop a compact data representation technique based on a hierarchical tensor-based transformation. In this technique, an original multi-dimensional dataset is transformed into a hierarchy of signals to expose its multi-scale structures. The(More)
In this paper we present a methodology and techniques for generating cycle-accurate macro-models for RT-level power analysis. The proposed macro-model predicts not only the cycle-by-cycle power consumption of a module, but the power profile of the module over time. The proposed methodology consists of three steps: module equation form generation and(More)
In this paper, an energy aware dynamic voltage and frequency selection (EA-DVFS) algorithm is proposed. The EA-DVFS algorithm adjusts the processor's behavior depending on the summation of the stored energy and the harvested energy in a future duration. Specifically, if the system has sufficient energy, tasks are executed at full speed; otherwise, the(More)
In this paper, we propose a statistical power evaluation framework at the RT-level. We first discuss the power macro-modeling formulation, and then propose a simple random sampling technique to alleviate the the overhead of macro-modeling during RTL simulation. Next, we describe a regression estimator to reduce the error of the macro-modeling approach.(More)
In this paper we present three efficient DVS techniques for an MPEG decoder. Their energy reduction is comparable to that of the optimal solution. A workload prediction model is also developed based on the block level statistics of each MPEG frame. Compared with previous works, the new model exhibits a remarkable improvement in accuracy of the prediction.(More)