Information-theoretic analysis of three-dimensional molecular integrated circuits

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Title: Information-theoretic analysis of three-dimensional molecular integrated circuits
Author: Lyshevski, Sergey
Abstract: For three-dimensional (3D) molecular integrated circuits (MICs), an information-theoretic model of signal processing is under developments in order. The objective is to estimate and examine the information-theoretic measures in order to perform optimization and carry out optimal design. Distinct information measures, such as entropy, capacity, complexity and other are analyzed. There is a need to derive baseline information estimates for 3DMICs to optimize molecular hardware and ensure a technology-centric co-design. This will allow us to approach fundamental limits and benchmarks. Three-dimensional MICs are envisioned to implement datapath, memory and other subsystems. For information measures, different quantitative and qualitative estimates can be utilized. The information-theoretic analysis imposes significant challenges due to mathematical complexity and technology dependence. The information analysis to correctly compute switching functions and maximize the mutual information examining channel input and output can be performed. However, digital versus analog solutions, switching frequency, thresholds, switching energy, power losses and other characteristics depend on logic design as well as dynamic and steady-state characteristics of molecular devices. Hence, the information-theoretic analysis should integrate hardware, software and fabrication technology. It is shown that critical information measures depend on data structures, and, the information content of channels are technology-dependent. Different molecular gates, comprised from multi-terminal primitives (molecular electronic devices), can be used to implement neuronal hypercells (hypercells). The aggregated hypercells form 3DMICs. This paper focuses on further developments of molecular electronics and molecular signal processing platforms by utilizing quantifying and qualifying information measures and optimizing information estimates.
Description: Copyright 2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
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Date: 2006-06

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