This course is perfect for students, engineers, and academicians who want to learn the basics of Digital Filters and how to design them in Python. It covers Finite Impulse Response (FIR) and Infinite Impulse Response (IIR) filters, with theory and practical implementation. With step-by-step instructions and plenty of examples, this course will give you the confidence to design filters for different DSP applications. It also covers the characteristics of DT-LTI systems and various FIR and IIR filter design techniques. Don't miss out on this opportunity to learn the fundamentals of Digital Filters and gain the skills to apply them in real-world scenarios.
Java Digital Signal Processing (DSP) From Ground Up™
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This course is designed to give you a solid foundation in the most useful aspects of Digital Signal Processing (DSP) in an engaging and easy to follow way. With a programming based approach, you will learn practical techniques while avoiding abstract mathematical theories. Using the Java programming language, you will develop algorithms such as the Convolution Kernel, Discrete Fourier Transform (DFT), Inverse Discrete Fourier Transform (IDFT), Finite Impulse Response (FIR) filters, Infinite Impulse Response (IIR) filters, Windowed-Sinc filters, Modified Sallen-Key filters, Bessel, Chebyshev and Butterworth filters, and the Fast Fourier Transform (FFT). By the end of this course, you will be able to build a complete DSP library in Java and even give a lecture on DSP. Take a look at the full course curriculum to learn more.
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