From 6f8091a1651c73a5005f6dc32e027e7238326926 Mon Sep 17 00:00:00 2001 From: Vipul Arora <6668940+vipular@users.noreply.github.com> Date: Mon, 1 Apr 2024 11:00:36 +0530 Subject: [PATCH] added PSP course --- index.md | 2 +- stuff/2024_PSP.md | 65 +++++++++++++++++++++++++++++++++++++++++++++++ teaching.md | 8 +++--- 3 files changed, 71 insertions(+), 4 deletions(-) create mode 100755 stuff/2024_PSP.md diff --git a/index.md b/index.md index aeb3def..3964923 100755 --- a/index.md +++ b/index.md @@ -21,7 +21,7 @@ I work on developing learning based methods mostly for audio processing (music, I received my B.Tech. and Ph.D. degrees in [Electrical Engineering](http://www.iitk.ac.in/ee/) from the [Indian Institute of Technology (IIT) Kanpur](http://www.iitk.ac.in/), India. My Ph.D. thesis was titled "[Analysis of Pitched Polyphonic Music for Source Transcription](https://drive.google.com/file/d/0By8wZfM49Y2ScC1vc2lVX0I1c1U/view)", where I worked on analyzing music audio to identify and transcribe different instruments/voices playing simultaneously. During postdoc at Oxford University (UK), I developed [speech recognition](https://www.youtube.com/watch?v=Tgr3Y_U9BsQ) systems using linguistic principles, with applications in automatic language teacher and speech recognition for low-resource languages. At Amazon in Boston (USA), I worked on audio classification for developing Alexa [home security](https://www.theverge.com/2018/9/20/17883428/amazon-alexa-guard-alarm-ring-smart-home-security-price) system, with research focusing on classification with imbalanced data. -### Research interests: +### Current Research interests: Speech, Music, Audio processing Machine learning: diff --git a/stuff/2024_PSP.md b/stuff/2024_PSP.md new file mode 100755 index 0000000..7a9cecb --- /dev/null +++ b/stuff/2024_PSP.md @@ -0,0 +1,65 @@ +# EE698K: Programming for Signal Processing (Fall 2024) + +**Units:** 3-0-0-0-9 (modular course; 3 hours lecture; total 9 credits)
+**Class timings:** MTh 12:00-13:15 (venue TBD)
+**Instructor:** Vipul Arora
+**Office hours:** After each class
+ +## Registration Note: +- It is a PG-only course, open to all EE PGs only. + + + +## Course Objectives: +Most of the research in signal processing is heavily computational. +Good programming skills are indispensable for good computational research. +The knowledge of data structures and algorithms is necessary for writing efficient and easy to understand codes. +With advacing computational technologies and infrastructure, it is even more important to know these concepts well for effective and efficient use. +The course will discuss basics of programming and basics of digital signal processing. + +This course is tailored specifically for EE PGs with limited programming experience. +We will use Python to implement the concepts we learn in this course. (Python is one of the most popular high-level languages highly recommended for researchers). +There will be theory classes as well as coding assignments. + +## Pre-requisites: +- None + +## Lecture Plan + +| Topics | No of weeks | +|--------------------------------------------------------------------------------------------------------------|-------------| +| Python basics | 1 | +| Abstract Data Types, Arrays | 1 | +| Linked Lists, Stacks and Queues | 2 | +| Trees and Binary Search Tree | 1 | +| Heaps, Sets, Hash Tables | 1 | +| Graphs and Dynamic Programming | 1 | +| Linear Time Invariant Systems, Fourier Transforms | 2 | +| Z-transforms, symbolic programming, Linear Constant Coefficient Difference Equations, Digital Filter Design | 2 | +| Applications in audio processing | 2 | + +## Grading Scheme +1. Quizzes and assignments – 50% +2. Mid-sem Exam – 20% +3. End-sem Exam - 30% + +### Plagiarism Penalty:
+As heavy as possible. Zero-tolerance policy. + +## References: +- This course will take excerpts from some standard books on data structures and algorithms, and digital signal processing. +- Textbook for signal processing: "Digital Signal Processing: A Computer-Based Approach" by Sanjit K. Mitra +- See my introduction to basics of Python [here](https://www.youtube.com/playlist?list=PLbtAaXHMto-vV3G334P1iuj_4P_-qyT3x). + +Books: +- “Data Structures and Algorithms” by A. V. Aho, J. E. Hopcroft, J. D. Ullman​ +- https://livebook.manning.com/book/grokking-algorithms/table-of-contents ​ +- Discrete time signal processing (3rd ed.) – by Oppenheim and Schafer +- Digital Signal Processing (4th ed.) – by Proakis and Manolakis +- The Scientist and Engineer’s Guide to Digital Signal Processing - by Steven W. Smith (Available online https://www.dspguide.com/pdfbook.htm) +- Think DSP: Digital Signal Processing in Python - by Allen B. Downey (Available online https://greenteapress.com/wp/think-dsp/) diff --git a/teaching.md b/teaching.md index 5eed7ad..19759c7 100644 --- a/teaching.md +++ b/teaching.md @@ -5,11 +5,13 @@ slug: /teaching --- ## Courses -* **2024 Spring**: (NEW): +* **2024 Fall**: (NEW): + * EE698K - Programming for Signal Processing [[link]](stuff/2024_PSP.md) +* **2024 Spring**: * EE952 - Introduction to Machine Learning (for e-masters) [[link]](stuff/2024_ML_emasters.md) -* **2024 Spring**: (NEW): +* **2024 Spring**: * EE798B - Data Structures and Algorithms for Electrical Engineers [[link]](stuff/2024_DSA.md) -* **2024 Spring**: (NEW): +* **2024 Spring**: * EE698R - Advanced Topics in Machine Learning [[link]](stuff/2024_ML2.md) * **2023 Fall**: * EE798P - Audio Representation Learning [[link]](stuff/2023_ARL.md)