This course provides the basic toolkit for any signal processing application - the abstraction of signals and systems, from the point of view of analysis and characterisation. We encounter signals and systems extensively in our day-to-day lives, from making a phone call, listening to a song, editing photos, manipulating audio files, using speech recognition softwares like Siri and Google now, to taking EEGs, ECGs and X-Ray images. Each of these involves gathering, storing, transmitting and processing information from the physical world. This course will equip you to deal with these tasks efficiently by learning the basic mathematical framework of signals and systems.
This course is divided into two parts. In the first part (EE210.1x), we explored the various properties of signals and systems, characterization of Linear Shift Invariant Systems, convolution and Fourier Transform. Building on that, in this part (EE210.2x) we will deal with the Sampling theorem, Z-Transform, discrete Fourier transform and Laplace transform. The contents of the first part are prerequisites for doing this part. Ideas introduced in this course will be useful in understanding further electrical engineering courses which deal with control systems, communication systems, power systems, digital signal processing, statistical signal analysis and digital message transmission. The concepts taught in this course are also useful to students of other disciplines like mechanical, chemical, aerospace and other branches of engineering and science.
What you'll learn:
- How to analyze the effect of sampling
- How to reconstruct signals from samples under certain conditions
- How to bring continuous and discrete independent variable systems together
- How to generalize the Fourier Transform for continuous and discrete
- Independent variable systems, using the Laplace and z- transforms
- High school mathematics: Sequence and series, algebra of complex numbers, basic trigonometry.
- Calculus: Differential and Integral calculus (single variable). Knowledge of differential equations is helpful but not required.
- Concepts from EE210.1x: Analysis of continuous and discrete signals and systems in the natural/time domain, convolution, Continuous time Fourier analysis - the continuous Fourier Series and Fourier transform.
This is an introductory course to Digital Signal Processing that can be taken at any time. The course deals with the fundamentals in addition to exploring techniques like filtering, correlation and Fourier analysis. There is an emphasis in applying DSP theory to practical problems.
Learn about the various ways we hear and perceive sound and how to improve technology and products for better communication. Communication acoustics include all branches of acoustics dealing with communication systems between humans, between humans and machines, and between machines (e.g. speech acoustics, electro acoustics, audio technology). The open online course introduces you to this topic giving an overview of the different branches of acoustics. The following renowned experts from each area of expertise, which are united in the TU9 alliance, combine their knowledge to communicate basic principles, and to highlight current applications in communication acoustics .