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ECE 695E Lecture 15: Conclusions and Outlook
25 Jan 2019 | Online Presentations | Contributor(s): Muhammad A. Alam
Outline Introduction Review of the lectures Conclusions
ECE 695E Lecture 14: Physics-based Machine Learning
24 Jan 2019 | Online Presentations | Contributor(s): Muhammad A. Alam
Outline Why and what of physics-based machine learning Example 1: Dropping a ball in the real world Example 2: Lake temperature distribution Approach 2: Structural Equation Modeling Conclusions
ECE 695E Lecture 13: Deep Learning, Karnaugh Mapping, and Unsupervised Classification
OutlineIntroductionA two input, single and multiple perceptron problemBackpropagation and coefficient fittingMachine learning and Karnaugh mappingOther forms of Machine Learning (Unsupervised, optical, quantum)Conclusions
ECE 695E Lecture 12: Basics of Machine Learning
OutlineMachine learning is an algorithm for “fast” curve fittingMachine learning and classification: Example 1Machine learning and classification: Example 2 Any function can be represented by machine learning approach Conclusions
ECE 695E Lecture 10: Big Data Classification by Principal Component Analysis
Outline Introduction Why do we need reduction in data dimension Theory of Principle Component Analysis Applications of Principle Component Analysis Conclusions
ECE 695E Lecture 9B: DOE Analysis by ANOVA
OutlineIntroduction to Analysis of Variance (Anova)Single factor Analysis of VarianceTwo factor AnovaGeneralized AnovaConclusions
ECE 695E Lecture 9A: DOE and Taguchi Experiments
09 Jan 2019 | Online Presentations | Contributor(s): Muhammad A. Alam
ECE 695E Lecture 8: Statistical Design of Experiments
18 Jan 2019 | Online Presentations | Contributor(s): Muhammad A. Alam
Outline:Context and backgroundSingle factor and full factorial methodOrthogonal vector analysis: Taguchi/Fisher modelCorrelation in dependent parametersConclusions
ECE 695E Lecture 7: Bootstrap, Cross-Validation, and Goodness of Fit
Outline Introdution Goodness of Fit: Adjusted R-square, AIC methods, etc. Cross-validation: Another way to compare models Bootstrap method to generation population properties based on sample characteristics Parametric vs. non-parametric distribution Conclusions
ECE 695E Lecture 6: Equation-free Scaling Theory for Design of Experiments
Outline: Introduction Buckingham PI Theorem An Illustrative Example Why does the method work Conclusions
ECE 695E Lecture 5: Design of Experiments Scaling of Theory of Equations
Outline Introduction Rules of scaling or nondimensionalization Scaling of ordinary differential equations Scaling of partial differential equations Equivalence of equations and solutions Conclusions
ECE 695E Lecture 4: Model Selection and Goodness of Fit
OutlineThe problem of matching data with theoretical distributionParameter extractions: Moments, linear regression, maximum likelihoodGoodness of fit: Residual, Pearson, Cox, AkikaConclusion
ECE 695E Lecture 3: Physical and Empirical Distributions
03 Jan 2019 | Online Presentations | Contributor(s): Muhammad A. Alam
OutlinePhysical Vs. empirical distributionProperties of classical distribution functionMoment-based fitting of dataConclusions
ECE 695E Lecture 2: Collecting and Plotting Data
OutlineReview of the traditional statistical metricsParametric vs. Nonparametric informationPreparing data for projection: Hazen formulaPreparing data for projection: Kaplan formulaConclusions
ECE 695E Lecture 1: Where do data come from?
OutlineA short history of dataAn example of small dataSmall vs. Big dataWhat to expect from the classConclusions
How to Write a Journal Paper
13 Dec 2017 | Online Presentations | Contributor(s): Muhammad A. Alam
A Tutorial Introduction to Negative-Capacitor Landau Transistors: Perspectives on the Road Ahead
04 Dec 2015 | Online Presentations | Contributor(s): Muhammad A. Alam
In this talk, I use a simple graphical approach to demystify the device and explain why the experimental results are easy to misinterpret. Since the NC-FET is just a special case of a much broader class of phase-change devices and systems (e.g., transistors, memories, MEMS, logic-in-memory...
[Illinois] How to Break the "Fundamental" Limits of Nanobiosensing
07 Apr 2014 | Online Presentations | Contributor(s): Muhammad A. Alam
As the future of Moore’s law of transistor scaling appears uncertain, electronics is being reinvented by broadening the focus to other areas including macroelectronics (electronics of large, possibly flexible and transparent displays), bioelectronics (e.g., nanobio sensors for genomics,...
Sequencing a Genome by a Torrent of Ions: How an Old pH-Meter Got Its Groove Back
11 Apr 2014 | Online Presentations | Contributor(s): Muhammad A. Alam
The ability to read the book of life, written in the genome of an organism, has been one of the most exciting development of our time. The first version of human genome was announced circa 2000 and it took a decade of industrial-scale collaboration and billions of dollars of funding. Today, we do...
nanoHUB-U: Principles of Nanoelectronic Biosensors Week One Scripts
10 Nov 2013 | Online Presentations | Contributor(s): Muhammad A. Alam
ECE 695A Lecture 40: Failure Analysis and Epilogue
07 May 2013 | Online Presentations | Contributor(s): Muhammad Alam
Outline:Plan experiments, test carefully, and then post-mortemSummary: NBTI, HCI, TDDB, RadiationSummary: Measurement and Data AnalysisSummary: Why I work on this fieldConclusion
ECE 695A Lecture 39-1R: Review Questions
01 May 2013 | Online Presentations | Contributor(s): Muhammad Alam
Review Questions:What is the difference between hard and soft error?What is typical charge loss mechanism for ZRAM ?The soft error in Flash memory is different from that of ZRAM. Explain.How do people accelerate radiation induced damage? If carrier relaxation was faster than thermionic emission...
ECE 695A Lecture 39-1: Radiation and Devices I
Outline:Introduction to ZRAMSoft Errors in Zero-capacitor RAMSoft Errors in in Flash memoriesHard Errors and Anomalous leakage in Flash memoryConclusions
ECE 695A Lecture 38R: Review Questions
29 Apr 2013 | Online Presentations | Contributor(s): Muhammad Alam
ECE 695A Lecture 38: Charge Generation by Particles