Thermal Noise Behavior of the Bridge Circuit

Abstract

This paper considers a connection between the deterministic and noisy behavior of nonlinear networks. Specifically, a particular bridge circuit is examined which has two possibly nonlinear energy storage elements. By proper choice of the constitutive relations for the network elements, the deterministic terminal behavior reduces to that of a single linear resistor. This reduction of the deterministic terminal behavior, in which a natural frequency of a linear circuit does not appear in the driving-point impedance, has been shown in classical circuit theory books. The paper shows that, in addition to the reduction of the deterministic behavior, the thermal noise at the terminals of the network, arising from the usual Nyquist-Johnson noise model associated with each resistor in the network, is also exactly that of a single linear resistor. While this result for the linear time-invariant (LTI) case is a direct consequence of a well-known result for RLC circuits, the nonlinear result is novel. We show that the terminal noise current is precisely that predicted by the Nyquist-Johnson model for R if the driving voltage is zero or constant, but not if the driving voltage is time-dependent or the inductor and capacitor are time-varying.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2000
Accession Number
ADA457849

Entities

People

  • Brian D. Anderson
  • Geoffrey J. Coram
  • John L. Wyatt Jr.

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Computer Science
  • Differential Equations
  • Electrical Engineering
  • Equations
  • Fokker Planck Equations
  • Frequency
  • Frequency Domain
  • Impedance
  • Information Science
  • Order Statistics
  • Partial Differential Equations
  • Probability
  • Random Variables
  • Short Circuits
  • Statistics
  • Steady State
  • White Noise

Readers

  • Control Systems Engineering.
  • Electronics Engineering
  • Mathematical Modeling and Probability Theory.