Nonlinearity and Information Processing

Abstract

Nonlinearity and Information Processing: The objective of this research is to design morphable logic gates with the potential to autonomously adaptable to optimize selected tasks such as pattern recognition. We propose to study and investigate the interplay and connection between nonlinear dynamics, and information and information processing. The goal of this proposal is twofold: 1. To understand how nonlinear dynamics is in principale connected to information processing and computation, and create a theoretical link between these two concepts. In this approach, we will develop new definitions and new measures for the amount of computation that a system can perform based on the dynamical features of that system. Shannon’s entropy, as a physical concept, is a well-known measure for the amount of information in a system. We will provide a similar bridge between concepts, but this time between physics and information processing. Furthermore, we will investigate how spatiotemporal dynamics can be connected to information processing, where information processing happens both temporally and spatially. 2. To utilize nonlinear dynamics and nonlinear techniques in order to gather information about phenomena that we otherwise would not be able to obtain. As examples, we will utilize nonlinear dynamics to: 1) obtain information about the behavior of stars that are thousands of light years away from us; and to 2) obtain information (a dynamical signature) of heart diseases, such as arrhythmogenic right ventricular cardiomyopathy, that are clinically difficult, if not impossible, to detect.

Document Details

Document Type
DoD Grant Award
Publication Date
Nov 23, 2016
Source ID
N000141613056

Entities

People

  • William L. Ditto

Organizations

  • North Carolina State University
  • Office of Naval Research
  • United States Navy

Tags

Readers

  • Computer Vision.
  • Distributed Systems and Data Platform Development
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms