L and L Optimal Downsampling from System Theoretic Viewpoint

Sampling from a system-theoretic viewpoint part II: noncausal solutions

This paper puts to use concepts and tools introduced in Part I to address a wide spectrum of noncausal sampling and reconstruction problems. Particularly, we follow the system-theoretic paradigm by using systems as signal generators to account for available information and system norms (L and L) as performance measures. The proposed optimization-based approach recovers many known solutions, der...

A sampled-data approach to optimal non-causal downsampling

Downsampling is the process of reducing the sampling rate of a discrete signal. This paper describes how sampled data system theory can be used to design an L2 or L∞ optimal downsampler which reduces the sampling rate by a positive integer factor from a given fast sampler. This paper also describes the effect of noise on the optimal downsampling.

System Theoretic Perspectives of the Sampling Theorem

In this paper we study the (classical) problem of reconstructing a continuous-time signal from its samples. We adopt a system-theoretical viewpoint of this problem. Namely, we assume that the continuous-time signal is modeled as the output of a linear time-invariant system and then formulate the reconstruction problem as the (either L or L) optimal model-matching problem in the lifted domain. T...

Sampling from a System-Theoretic Viewpoint

This paper studies a system-theoretic approach to the problem of reconstructing an analog signal from its samples. The idea, borrowed from earlier treatments in the control literature, is to address the problem as a hybrid model-matching problem in which performance is measured by system norms. The paper is split into three parts. In Part I we present the paradigm and revise the lifting techniq...

Fuzzy sets form A meta-system-theoretic point of view