A Refresher experiential course on linear algebra and Optimization for Most Modern Signal processing and pattern classification
2511,2611 and 2711, 2017 Centre for Excellence in Computational Engineering and Networking (CEN), Amrita Vishwa Vidyapeetham (Amrita University).
About MSP 2017 Workshop
The objective of this workshop is to make the students especially B.Tech students ready for the new generation jobs. Many universities are now offering courses with electives from various subject domains to mould their students to meet the requirements of the industry. So, to bring interdisciplinary experimental active learning in our University, Center for Computational Engineering and Networking is organizing a 3day course to reinforce linear algebra and optimization through experiments for modern signal processing and pattern classification.
Venue: CEN class room
Registration is closed
Recent Talks given by CEN faculties
Check out the earlier workshops conducted by CEN
Why we conduct workshop frequently? Advancement in technologies make many conventional engineering syllabus obselete
Program
25112017
9.00 AM to 5 PM (please find below the detailed schedule)
Linear algebra fundamentals and computational experiments with Matlab and Python  Dr. K. P. Soman
Linear algebra, optimization (multivariate calculus + algorithms) and probabilistic graphical models have now become most essential subjects needed to tackle the problems in the era of automation and data science. The common complaints to students regarding Linear algebra are

It is very abstract;

It contains too many new concepts; and

They donâ€™t know what uses it has.
One possible and viable solution at hand is
Use Computational experiments to investigate and reinforce the concepts. Use Matlab as a Mathematical Laboratory. Example applications are plenty and are easy to demonstrate with in Matlab Environment. As the student progress from first year to fourth year, faculty may expose the students to newer and tougher problems and experiments. Most design and control problems in any Engineering are now tackled with above core subjects.
Years of acquaintance with students from various disciplines admitted to M.Techs, it is observed that , for many, Matrix is a a balck box. It simply is a rectangular array of numbers for them. They know the rules for finding certain quantities like determinant, eigenvalues and eigenvectors associated with a square matrix. Most of them could not tell a single application of these concepts.
So, finally for many, Advanced Mathematics means :
A collection of rules if followed as per instruction proposed by teacher give solution to some well defined problems formulated by somebody (mainly the reference books authors).
This view need to be changed. The universe and its laws are described mainly by nonlinear equations. Understanding nature of its behavior demands computational experiments.
Some of the concepts missed by B.Tech graduates in Linear Algebra are.
1. Matrix vector multiplication has two interpretations.
1.1 Dot product interpretation
1.2 Linear Combination interpretation
2. MatrixMatrix multiplication has four interpretations / visualizations
2.1 An ordered sequence of dot products
2.2 Ordered Column wise linear combinations
2.3 Ordered row wise linear combinations
2.4 Sum of columnrow outer products (sum of rank1 matrices)
3. Understanding SVD properly helps in understanding
3.1 How Google search engine works
3.2 How simple Steganography and Watermarking works etc
4. The concept of Leastnorm solution and PseudoInverse
5. Concept of Orthogonality of functions and vectors and its use in Signal in Signal/ image processing and Communication Engineering. The lack of knowledge include principle behind the creation of
5.1 Real discrete Fourier basis matrix
5.2 Discrete Cosine Bases
5.3 Walsh Hadamard bases
5.4 Complex Fourier bases
5.5 infinite such orthogonal bases using wavelet theory.
6. Digital Signal processing with the help of orthogonal matrices Filtering and removing specific components
7. Fundamental subspaces associated with a matrix and creation of their bases
8. Concept of Quadratic polynomials and characterization by signs of eigenvalues
In this workshop we aim to discuss and offer computational experiments in matlab/python so as to get a firm grip on the tougher concepts in linear algebra and to show how to use Linear algebra and basic optimization theory for signal processing and pattern classification.
26112017
Advanced liner algebra  Dynamic Mode Decomposition and its applications
9.00 AM to 5 PM
Topics which will be discussed in this session
 Dynamic mode decomposition: An introduction  Dr. K. P. Soman
 Fluid dynamics  Dr. E.A Gopalakrishnan
 Koopman Analysis  Dr. K. P. Soman
 Epidemiology  Mr. Barathi Ganesh H B
 Koopman operators for power systems  Ms. Suchithra K.S
 Video processing  Mr. Sachin Kumar S and Ms. Sikha O.K
 Multiresolution DMD  Ms. Neethu Mohan
 DMD with control  Ms. Sanjanashree J.P and Ms. Athira Gopalakrishnan
 Delay coordinates  ERA and HMM  Mr. Premjith B
 Noise and power  Mr. Jyothish Lal G
 Sparsity and DMD  Ms. Manjusha K, Mr. Nidhin Prabhakar T.V and Ms. Ganga Gowri B
 DMD on nonlinear observables  Dr. K. P. Soman
 Neuroscience  Ms.Pravena D
 Financial trading  Mr. Nidhin Unnithan
Books published from CEN on Signal processing and Machine learning
1. Dr. K.P. Soman, Prabaharan Poornachandran, Sachin Kumar S and Neethu Mohan, "Convex Optimization based Signal Processing for IOT." [Upcoming Book]
2. Dr. K.P. Soman and Dr. Ramachandran K.I, "Insight into Wavelets From Theory to Practice.", PrenticeHall India 2004.
3. Dr. K.P. Soman, Shyam Diwakar, Ajay V., "Insight into Data Mining From Theory to Practice.", PrenticeHall India, 2006.
4. Dr. K.P. Soman, Ajay. V, Loganathan R., "Machine Learning with SVM and other Kernel Methods.",PrenticeHall India, 2009.
5. Dr. K.P.Soman, and Ramanthan, "Digital signal and Image ProcessingThe Sparse Way." Elsevier Publications, 2012.
6. Dr. Deepa G., Dr. Krishnan Namboodiri, "Bioinformatics: Sequential and Structural Analysis.", Narosa Publications.
7. Dr. K.I Ramachandran., Dr. Deepa, Dr. Krishnan Namboori, "Computational Chemistry and Molecular Modelling." Springer international.
8. "Fractals for Everyone." [Online version](http://cen.amritafoss.org/downloads/) Manu Unni, Praveen Krishnan, Dr. K. P. Soman.