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In this paper, we study nonparametric density estimation by the histogram method. Histogram is interpreted as quantization, which decreases the amount of information. Then interpolation (or estimation) of the missing information is needed. To achieve this, we introduce sampled-data H2/Hinfin optimization. We design the reconstruction system which optimizes the worst case error between the original...
In this paper, we consider signal interpolation of discrete-time signals which are decimated nonuniformly. A conventional interpolation method is based on the sampling theorem, and the resulting system consists of an ideal filter with complex coefficients. On the other hand we adopt sampled-data Hinfin optimization, which can take account of intersample behavior, and the optimal filter with real coefficients...
Spline interpolation systems generally contain non-causal filters, and hence it is difficult to use such systems for real-time processing. Our objective is to design a causal system which approximates spline interpolation. This is formulated as a problem of designing a stable inverse of a system with unstable zeros. For this purpose, we adopt H alpha optimization. The Halpha-optimal inverse system...
In this paper, we propose a new method for designing oversampling DeltaSigma DA converters via Hinfin optimization. The design consists of two steps. One is that for DeltaSigma modulators. In DeltaSigma modulators, the accumulator 1/(z - 1) is conventionally used in a feedback loop to shape quantization noise. In contrast, we give all stabilizing feedback filters for the modulator, and propose an...
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