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• W3016075618 abstract "Analog signals processed in digital hardware are quantized into a discrete bit-constrained representation. Quantization is typically carried out using analog-to-digital converters (ADCs), operating in a serial scalar manner. In some applications, a set of analog signals are acquired individually and processed jointly. Such setups are referred to as distributed quantization. In this work we propose a distributed quantization scheme for representing a set of sparse time sequences acquired using conventional scalar ADCs. Our approach utilizes tools from secure group testing theory to exploit the sparse nature of the acquired analog signals, obtaining a compact and accurate representation while operating in a distributed fashion. We then show how our technique can be implemented when the quantized signals are transmitted over a multihop communication network providing a low-complexity network policy for routing and signal recovery. Our numerical evaluations demonstrate that the proposed scheme notably outperforms conventional methods based on the combination of quantization and compressed sensing tools." @default.
• W3016075618 created "2020-04-17" @default.
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• W3016075618 date "2020-05-01" @default.
• W3016075618 modified "2023-09-23" @default.
• W3016075618 title "Distributed Quantization for Sparse Time Sequences" @default.
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• W3016075618 doi "https://doi.org/10.1109/icassp40776.2020.9054339" @default.
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