Introduction: Electronic Hardware Design – Requirement and Challenges, Overview of Design tools (LTSPICE, Microcontroller usage and coding, PCB Design softwares)

Stage 1: Design, Simulation, Analysis and Implementation of a typical (analog + digital) electronic module. Realization and testing of a bread-boarded model, followed by PCB schematic design. Fabrication of PCB using etching machine. Preferably Two students in a batch

Stage 2: Execution of an electronic design case study (preferably individual projects) and demonstrate its real-time working and applications.

Overview of CMOS device fundamentals (DC Characteristics, AC Characteristics, Processing overview). CMOS inverters, Static and Dynamic characteristics, Dynamic behavior, transition time, Propagation Delay, Power Consumption. MOS Circuit Layout & Simulation, Stick diagrams, Layout design rules, MOS device layout, Transistor layout, Inverter layout, circuits layout Combinational logic, Static MOS, Complementary MOS, Ratioed logic, Pass Transistor logic, Complex logic circuits, DSL, DCVSL, Transmission gate logic. Dynamic MOS design, Dynamic logic families and their performance.

Basic MOS device. Overview of non-ideal behaviour of deep sub-micron MOS transistors. Analysis and design of current mirrors and current sources. Analysis and design of single stage amplifiers, differential amplifiers: Small signal analysis, frequency response, noise, linearity. Analysis and design of OTA circuits – differential pair, cascodes, folded-cascodes, two-stage OTAs. Stability, frequency compensation, MRR, PSRR. Feedback. Fully differential op-amps, CMFB. Bandgap references. Output stages. Switched-capacitor circuits, comparators.

Broad-stroke overview – History of Microsystem Technology with overview on commercial products, Sensing & Actuation Principles of Microsystems, Applications-MEMS Materials and Fabrication Technology Microelectronic technologies for MEMS, Micromachining Technology: Surface and Bulk Micromachining, -Design and modelling of MEMS/Microsystem: Mechanics of MEMS/Microsystems- Elasticity-Stress/strain analysis of beams, membranes etc., thin film stress-Dynamics of Microsystems MEMS Transduction Mechanisms: Optical, piezoelectric, piezoresistive, FET based transduction etc.

Review of quantum mechanics, E-K diagrams, effective mass, electrons and holes in semiconductors, band diagram of silicon, carrier concentration, carrier statistics, carrier transport, junction devices(P-N junction, Metal –semiconductor junctions, solar cells etc.), MOS capacitor as a building block for MOSFETs (Ideal MOS, real/Non ideal MOS, band diagrams, C-V characteristics, electrostatics of a MOSCAP), MOSFET, I-V characteristics, scaling, short channel and narrow channel effects, high field effects, Reliability of transistor.

Multidisciplinary Design Optimization (MDO): Need and importance – Coupled systems – Analyser vs. evaluator – Single vs. bi-level optimisation – Nested vs.

Kernel Methods: reproducing kernel Hilbert space concepts, kernel algorithms, multiple kernels, graph kernels; multitasking, deep learning architectures; spectral clustering ;model based clustering, independent component analysis; sequential data: Hidden Markhov models; factor analysis; graphical models; reinforcement learning; Gaussian processes; motiff discovery; graph based semi supervised learning; natural language processing algorithms.

Introduction to data mining concepts; linear methods for regression; classification methods: k- nearest neighbor classifiers, decision tree, logistic regression, naive Bayes, Gaussian discriminant analysis; model evaluation & selection; unsupervised learning: association rules; apriority algorithm, FP tree, cluster analysis, self- organizing maps, google page ranking; dimensionality reduction methods: supervised featureselection, principal component analysis; ensemble learning: bagging, boosting, Ada Boost; outlier mining; imbalance problem; multi class classification; evolutionary comp

Optimization: need for unconstrained methods in solving constrained problems, necessary conditions of unconstrained optimization, structure methods, quadratic models, methods of line search, steepest descent method; quasi-Newton methods: DFP, BFGS, conjugate-direction methods: methods for sums of squares and nonlinear equations; linear programming: sim- plex methods, duality in linear programming, transportation problem; nonlinear programming: