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This paper presents novel results on scalar feedback quantization (SFQ) with uniform quantizers. We focus on general SFQ configurations where reconstruction is via a linear combination of frame vectors. Using a deterministic approach, we derive two necessary and sufficient conditions for SFQ to be optimal, i.e., to produce, for every input, a quantized sequence that is a global minimizer of the 2-norm...
In this paper we consider the problem of identification of linear systems using quantized data. We argue that, where possible, it is desirable to not utilize "naively" quantized data but instead it is preferable to choose the quantization mechanism carefully. In particular, we show that using a generalized noise shaping coder improves the accuracy of the estimates. We examine the accuracy...
This paper presents novel results on the joint problem of sampling, reconstruction and quantization of analog signals. Existing literature on this topic deals exclusively with band-limited signals in sampled form. Our key departure from earlier results is that we deal with continuous time reconstruction of not necessarily band-limited signals. Our approach utilizes concepts and tools from optimal...
This paper presents novel results on the joint problem of sampling and quantization of non bandlimited signals. Existing literature typically focuses either on sampling in the absence of quantization, or, conversely, studies quantization for already sampled signals. Our emphasis here is on the issues that arise al the intersection of these two design problems. We argue that the joint problem can be...
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