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UID:20260908T055100EDT-0720kxRdMt@132.216.98.100
DTSTAMP:20260908T095100Z
DESCRIPTION:Abstract\n\nElectrical noise sets a fundamental limit on the pe
 rformance of electronic systems\, particularly in high-sensitivity applica
 tions such as radio-frequency receivers. As circuit complexity continues t
 o grow\, there is a critical need for faster and more scalable noise analy
 sis methods in circuit simulators. Although time-domain transient noise an
 alysis offers broader applicability than frequency-domain and time-domain 
 steady-state noise analysis\, it is typically more computationally expensi
 ve\, especially for large circuits. This challenge is intensified by flick
 er noise\, whose inclusion in a time-domain circuit formulation greatly in
 creases the effective size of the system. To address these efficiency prob
 lems\, this dissertation presents several transient noise analysis methods
 . Using parallel computing and innovative continuous-time and discrete-tim
 e modeling approaches\, these methods achieve significant improvements in 
 computational efficiency compared to state-of-the-art methods.\n\nCovarian
 ce analysis is an effective technique for simulating transient noise in sm
 all subblocks of larger circuit designs due to its accuracy and reasonable
  simulation times. However\, its computational efficiency deteriorates as 
 circuit size increases. To improve scalability and reduce simulation times
 \, this dissertation first presents a parallel covariance analysis method.
  It also introduces a new flicker noise time-domain circuit representation
  that mitigates the added system complexity associated with modeling flick
 er noise sources in covariance analysis. Furthermore\, an adjoint-based ap
 proach is offered to improve the computational efficiency of the parallel 
 covariance analysis method. This dissertation then presents a charge-based
  covariance analysis method that models nonlinear capacitors using charge 
 rather than voltage in a linearized time-domain noise-perturbed circuit fo
 rmulation. This approach achieves higher numerical accuracy than tradition
 al capacitance-based methods\, allowing larger simulation step sizes and c
 onsequently reducing simulation times. Finally\, a charge-based covariance
  analysis method derived using implicit numerical schemes for stochastic d
 ifferential equations is introduced. By modeling the discrete-time evoluti
 on of the covariance\, this method provides a more computationally efficie
 nt and scalable alternative to continuous-time formulations.\n
DTSTART:20260526T130000Z
DTEND:20260526T150000Z
LOCATION:Room 603\, McConnell Engineering Building\, CA\, QC\, Montreal\, H
 3A 0E9\, 3480 rue University
SUMMARY:PhD defence of Alex Goulet – Covariance-Based Methods for Computati
 onally Efficient Transient Noise Analysis in Electronic Circuits
URL:https://www.mcgill.ca/ece/channels/event/phd-defence-alex-goulet-covari
 ance-based-methods-computationally-efficient-transient-noise-analysis-3728
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