Learn · Modeling Stochastic phenomena for Engineering applications: Part-1
Lecture 5 of 63week-01
Week 1: Lecture 5: Laplace Transforms & Convolution theorem
Prof. Yelia Shankaranarayana Mayya · IIT Bombay
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- Modeling Stochastic phenomena for Engineering applications: Part-1, IIT Bombay (at NPTEL)
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All the lectures
- Week1: Lecture1: Stirling’s Approximation
- Week 1: Lecture 2: Fourier Transforms and characteristic function.
- Week 1: Lecture 3: Dirac Delta function
- Week 1: Lecture 4: Applications of delta function and Generating functions.
- Week 1: Lecture 5: Laplace Transforms & Convolution theorem
- Week 2: Lecture 6: Generating function for discrete variables and Binomial distribution
- Week 2: Lecture 7: Bernoulli and Poisson distributions
- Week 2: Lecture 8: Waiting time distributions; Gaussian approximation to Poisson distribution
- Week 2: Lecture 9: Introduction to Central Limit Theorem
- Week 2: Lecture 10: Proof of Central Limit Theorem (CLT)
- Week 3: Lecture 11: Universality of Normal distribution and Exceptions
- Week 3: Lecture 12: Introduction to Random Walk: Extension of Central Limit Theorem
- Week 3: Lecture 13: Random walk and Diffusion coefficient: Conditional and Transition
- Week 4: Lecture 14: Characteristics of Stochastic Phenomena: Markov Processes
- Week 4: Lecture 15: Propagating Markov processes via Transition Probability Matrix with
- Week 4: Lecture 16: Chapman-Kolmogorov Equation for Multistep Transition probability and solution...
- Week 4: Lecture 17: Transient solutions and Continuous time Markov process
- Week 5: Lecture 18: Exact solution to Symmetric (or unbiased) one-dimensional Random walk (1-D RW)..
- Week 5: Lecture 19: Properties of the solution for 1-D unbiased RW
- Week 5: Lecture 20: 1-D unbiased RW: Asymptotic form of occupancy probability and transition ...
- Week 6: Lecture 21: Solution to the problem of 1-D Random Walk with Bias
- Week 6: Lecture 22: Generalized Random Walk with Bias and Pausing
- Week 6: Lecture 23: Effect of Pausing on Mean and Variance of Random walk
- Week 6: Lecture 24: Random-walk in the presence of reflecting barrier
- Week 6: Lecture 25: Boundary conditions for reflected Random-Walk and formulating absorbing ...
- Week 6: Lecture 26: The survival probability and first-passage time distribution for Random walker..
- Week 6: Lecture 27: Random Walk with Bias and Absorber
- Week 6: Lecture 28: Drift and Survival probability for Random walk with bias and absorber
- Week 7: Lecture 29: Introduction to gambler’s ruin problem
- Week 7: Lecture 30: Solution for ultimate winning probability in Gambler’s ruin problem
- Week 7: Lecture 31: Solution to gambler’s ruin problem with site dependent jump probabilities
- Week 7: Lecture 32: Fourier transform method of solving lattice Random walks
- Week 7: Lecture 33: Two and higher dimensional Random walks
- Week 7: Lecture 34: Formulating the problem of Probability of Return to the origin
- Week 7: Lecture 35: Relationship between occupancy probability and first-time-return probability
- Week 8: Lecture 36: Proof of Polya’s theorem on the probability of return
- Week 8: Lecture 37: Return probability estimates in various dimensions and effect of bias in 1-D
- Week 8: Lecture 38: Dependence of first time return probability (Fk) on steps
- Week 8: Lecture 39: Equilibrium solutions in lattice random walk models
- Week 8: Lecture 40: Equilibrium solution to Ehrenfest’s flea model
- Week 9: Lecture 41: Differential equation formulation of stochastic phenomena
- Week 9: Lecture 42: Derivation of Fokker-Planck equation
- Week 9: Lecture 43: Generalized transition probability functions for Fokker-Planck equation
- Week 9: Lecture 44: Solution to 1-D Fokker-Planck equation for free particle: Method of Fourier...
- Week 9: Lecture 45: General non-gaussian solution to translationally invariant Chapman-Kolmogorov...
- Week 10: Lecture 46: Cauchy distribution, power-law and other non-gaussian solutions
- Week 10: Lecture 47: Wiener process and solution to absorbing barrier problems from Fokker-Planck...
- Week 10: Lecture 48: Application of Fourier Sine transform for single absorber problem
- Week 10: Lecture 49: Setting up Langevin equation for velocity fluctuations of Brownian particles
- Week 10: Lecture 48: Application of Fourier Sine transform for single absorber problem
- Week 10: Lecture 49: Setting up Langevin equation for velocity fluctuations of Brownian particles
- Week 10: Lecture 50: Understanding the origin of systematic and random parts of force from kinetic..
- Week 11: Lecture 51: Kinetic derivation of a formula for delta-correlated random force
- Week 11: Lecture 52: Mean square velocity, thermal equilibrium and relationship between relaxation..
- Week 11: Lecture 53: Velocity autocorrelation in Brownian motion
- Week 11: Lecture 54: Derivation of Stokes-Einstein relationship between diffusion coefficient and...
- Week 11: Lecture 55: Alternative derivation of Stokes-Einstein relationship & Brownian motion with..
- Week 12: Lecture 56: Numerical simulation of the Langevin equation
- Week 12: Lecture 57: Derivation of Klein-Kramers equation from Langevin equation for joint...
- Week 12: Lecture 58: Illustrative solutions to the Klein-Kramers equation
- Week 12: Lecture 59: Numerical simulation: Sampling from general distributions and Central...
- Week 12: Lecture 60: Numerical simulation of Random walk trajectories and method of solving Fokker..
- Live Session 05-03-2024