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Tentative Schedule of Lectures: EECS 219A, Fall 2014


September 2014

2014/09/03 (Wed):
  • 1-2:30 and 4-5: Syllabus and logistics. Introduction. Modelling basic circuit elements: linear resistor, capacitor, inductor, controlled sources, independent sources. Linearity and memorylessness. Nonlinear elements.

2014/09/08 (Mon):

2014/09/10 (Wed):
2014/09/15 (Mon):

2014/09/17 (Wed):
2014/09/22 (Mon):
  • 1-2:30: Circuit equation formulations (contd.): nodal analysis and modified nodal analysis by example. Standard DAE form. KVL and KCL using incidence matrices. Formulating Sparse Tableau in general.

2014/09/24 (Wed):
2014/09/29 (Mon):
  • 1-2:30: DAEs with inputs and outputs. SPICE netlist syntax; parsing and equation setup. Glimpse of mechanical and biological "netlists". Quiescent steady state and NR: introduction.
October 2014

2014/10/01 (Wed):
2014/10/06 (Mon):

2014/10/08 (Wed):
2014/10/13 (Mon):
  • 1-2:30: Jacobian sparsity continued: how sparse graph structure translates to sparse Jacobians for STA and MNA equations. Numerical solution of linear equation systems: Gaussian Elimination.

2014/10/15 (Wed):
2014/10/20 (Mon):
  • 1-2:30: Matrix conditioning and error amplification in Ax=b solution (contd.). Ax=b error growth in LU factorization. Pivoting for controlling error growth. Simple iterative techniques for linear solution.

2014/10/22 (Wed):
  • 1-2:30 and 4-5: When to use iterative linear methods over direct. Basic data structures for sparse matrices. Summary of pitfalls in Ax=b solution. Sparse matrix packages. Biochemical reaction pathways. Rate equations, conservation, equilibrium for unimolecular reactions. Eigenanalysis of unimolecular reactions.
2014/10/27 (Mon): (lecture by Aadithya)
  • 1-2:30: Bimolecular reactions. Rate equations for multi-molecular reactions. Stoichiometry. Enzyme-catalyzed reactions and their ))Michaelis-Menten(( approximations.


2014/10/29 (Wed):MIDTERM EXAM
  • 1-2:30 and 4-5: MIDTERM exam. Midterm solution/discussion.
November 2014

2014/11/03 (Mon):

2014/11/05 (Wed): (lectures by Aadithya)
  • 1-2:30 and 4-5: Numerical solution of ODEs. Existence and uniqueness conditions. Time-axis discretization. Towards numerical methods for ODEs: approximating solutions using piecewise polynomials. FE, BE and TRAP methods.
    • video of 1-2:30pm lecture.
    • [https://draco.eecs.berkeley.edu/videos/2014-Fall-219A/2014-Nov-05EE219A-introducing-FE-BE-TRAPcontinued.html|video of 4-5pm lecture].


2014/11/10 (Mon):
2014/11/12 (Wed):
2014/11/17 (Mon):
  • 1-2:30: Periodic steady state analysis of LTI systems. LTI DAEs. Linearization of nonlinear systems about quiescent steady states. Small-signal sinusoidal (SSS, aka "AC") analysis. Connection with Laplace-domain analysis. AC frequency sweeps.

2014/11/19 (Wed):
  • 1-2:30 and 4-5: Transfer function eigenanalysis: numerical-analytical procedure for obtaining the transfer function of LTI DAE systems in the Laplace domain. Poles and residues. Parameter sensitivity analysis of QSS/DC operating points. Linearization of parameter dependence. Expression for the DC sensitivity matrix.
2014/11/24 (Mon):
  • 1-2:30: Density of the DC sensitivity matrix. Computing the sensitivity matrix directly via LU factorization and its cost. Adjoint sensitivity computation. Introduction to noise analysis. Intuitive notions of noise. Probability and random variables primer: Sampling a random variable. Histograms.

2014/11/26 (Wed):
  • 1-2:30 and 4-5: From histograms to probability density functions. Gaussian and uniform distributions. Mean and variance derived from PDFs. PDFs of functions of RVs. Simultaneous sampling of several RVs - joint probabilities. Independence and correlation. Jointly Gaussian PDF.
December 2014

2014/12/01 (Mon):
  • 1-2:30: Stochastic processes primer: random variables as functions of time. Point-by-point and waveform ensemble views. Stationarity. Ergodicity. Stationary variance as average noise power. Autocorrelation function of a stationary stochastic process. Power spectral density. White noise.

2014/12/03 (Wed):
  • 1-2:30: Thermal, shot and flicker noise. Propagation of stationary noise through LTI systems. Vector stochastic processes. Stationary noise computation for LTI systems: direct and adjoint methods.