Classical scaling in CMOS, Moore’s Law, Clean room concept, Material properties,crystal struc- ture, lattice, Growth of single crystal Si, Cleaning and etching, Thermaloxidation, Dopant diffu- sion in silicon, Deposition & Growth (PVD, CVD, ALD,epitaxy, MBE, ALCVD etc.),Ion-im- plantation, Lithography (Photolithography, EUVlithography, X-ray lithography, e-beam lithog- raphy etc.), Etch and Cleaning, CMOSProcess integration, Back end of line processes (Copper damascene process, Metalinterconnects; Multi-level metallization schemes), Advanced technol- ogies(SOIMOSFETs, Strained Si, Silic

Basics: Control system representations, System stabilities, Coprime factorization and stabilizing controllers, Signals and system norms Modelling of uncertain systems: Unstructured Uncertain- ties, Parametric uncertainty, Linear fractional transformation, Structured uncertainties.

Robust design specifications: Small gain theorem and robust stabilization, Performance con- siderations, Structured singular values.

Design: Mixed sensitivity optimization, 2-Degree of freedom design, Sub-optimal solutions, Formulae for discrete time cases.

Introduction and historical background, Microsensors : Sensors and characteristics, Integrated Smart sensors, Sensor Principles/classification-Physical sensors (Thermal sensors, Electrical Sensors, tactile sensors, accelerometers, gyroscopes , Proximity sensors, Angular displacement sensors, Rotational measurement sensors, pressure sensors, Flow sensors, MEMS microphones etc.), Chemical and Biological sensors (chemical sensors, molecule-based biosensors, cell-based biosensors), transduction methods(Optical, Electrostatic, Electromagnetic, Capacitive, Piezoelectric, piezoresistive etc.), Mic

Soft switching Converters: Switching loss, basic principles of hard and soft switching.

Evolution of resonant converter topologies. Resonant Load Converters: analysis of series, parallel, LCC and LLC topologies. Resonant Switch Converters (quasi resonant). Resonant Transition Converters- phase modulated topologies, Soft Switched low power high frequency converters
with Auxiliary Switch. Emerging trends in low power high frequency soft switched converters.

Module 1: Role of Interface Electronics, Analog Electronic Blocks, OPAMP – internal structure, Open-loop gain, Input R, Output R, DC noise sources and their drifts, CMRR, PSRR, Bandwidth and stability, Slew rate, Noise – general introduction,OPAMP Circuits and Analysis - Difference and Instrumentation Amplifiers (3-opamp and 2-opamp), Effect of cable capacitance and wire-re- sistance on CMRR, IA with guards, Biomedical application, Current-mode IA (Howland), Current- input IA, filters, Filters with underdamped response, state-variable filters, All-pass filters, Current Sour

Machine learning basics: capacity, overfitting and underfitting, hyperparameters and validation sets, bias & variance; PAC model; Rademacher complexity; growth function; VC-dimension; fundamental concepts of artificial neural networks; single layer perceptron classifier; multi- layer feed forward networks; single layer feed-back networks; associative memories; introduc- tory concepts of reinforcement learning, Markhov decision process.

Optimization: need for unconstrained methods in solving constrained problems, necessary con- ditions of unconstrained optimization, structure methods, quadratic models, methods of line search, steepest descent method; quasi-Newton methods: DFP, BFGS, conjugate-direction meth- ods: methods for sums of squares and nonlinear equations; linear programming: simplex meth- ods, duality in linear programming, transportation problem; nonlinear programming: Lagrange multiplier, KKT conditions, convex programing

Linear Algebra: n- dimensional Euclidean spaces, linear transformation, Matrices, Eigen values and Eigen vectors, Generalised inverses, SVD.

Numerical Methods: Numerical Solution of nonlinear equations, Direct and iterative methods to solve system of linear equations, Numerical integration – Trapezoidal and Simpson’s rule, Interpolation, Splines and curve fitting, Numerical solution of ODE – Euler’s method and 4th order Runge- Kutta Method.

Dynamic model of DC-DC converters in DCM: averaged switched model, small signal model- ling of the low frequency model. High frequency dynamics of converter operating in DCM.

Forced commutated AC-AC converters – Matrix Converters: operation, topologies, commutation strategies, voltage modulation – Direct and Indirect schemes.Dynamic model, design of passive elements and control scheme.

Basic Concepts of dynamical systems and stability.Modelling of power system components for stability studies: generators, transmission lines, excitation and prime mover controllers, flexible AC transmission (FACTS) controllers.

Introduction: Nonlinear system behavior, Nonlinear control.

Basic mathematical concepts: Finite dimensional optimization, Infinite dimensional optimization, Con- ditions for optimality, Performance measures for optimal control problems. Dynamic programming: The optimal control law, The principle of optimality, Dynamic programming concept, Recurrence relation, computational procedure, The Hamilton-Jacobi-Bellman equations.