Wave Mathematics with Neural Networks
Visualize wave dynamics and mathematical patterns using neural networks to reveal underlying wave behavior and propagation characteristics.
Visualize wave dynamics and mathematical patterns using neural networks to reveal underlying wave behavior and propagation characteristics.
This intermediate-level pilot course presents a unified approach to understanding wave phenomena through neural networks. Students explore the mathematical foundations of various wave types, from acoustic to electromagnetic, using neural networks as visualization tools. The curriculum bridges different physical systems by emphasizing their common mathematical structure, making complex wave equations more accessible and intuitive.
Instructors:
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What you'll learn
Understand how diverse oscillatory systems share common mathematical structures
Visualize wave equations using neural network representations
Analyze wave systems formed by coupled oscillators
Perform quantitative calculations of source-generated waves
Skills you'll gain
This course includes:
Live video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
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There are 4 modules in this course
This innovative course unifies different wave phenomena through their common mathematical structure. Beginning with fundamental oscillator systems, students learn how diverse physical systems share underlying mathematical principles. The course uses neural networks as a visualization tool to make complex wave equations more intuitive and accessible. Through quantitative examples and practical applications, students gain a deeper understanding of wave behavior across different physical domains.
Math and the Physical World, Exponential and Oscillatory Response
Module 1
More Oscillator Examples and Responses
Module 2
Oscillators to Waves and Normal Modes
Module 3
Transmission Lines, Guitars, and Dipole Antennas
Module 4
Fee Structure
Instructor
8 Courses
Pioneering Nanoscale Electronics Innovator
Supriyo Datta is the Thomas Duncan Distinguished Professor of Electrical and Computer Engineering at Purdue University, whose groundbreaking contributions have transformed the field of nanoelectronics. Initially starting his career in ultrasonics, he shifted his focus to nanoscale electronic devices in 1985, where he developed revolutionary approaches to quantum transport. His pioneering work combines the non-equilibrium Green function (NEGF) formalism with the Landauer formalism, which has become a cornerstone in nanoelectronics research. His influential books, including "Electronic Transport in Mesoscopic Systems" (1995), "Quantum Transport: Atom to Transistor" (2005), and "Lessons from Nanoelectronics" (2012), have shaped the field's theoretical foundation. His innovative theoretical proposals have sparked new research areas in molecular thermoelectricity, negative capacitance devices, and spintronics, leading to his election to the National Academy of Engineering (NAE)
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