Java Digital Signal Processing (DSP) From Ground Up™

What you'll learn
Build a Complete DSP Library in Java
Develop the Convolution Kernel algorithm in Java
Develop the Discrete Fourier Transform (DFT) algorithm in Java
Master Efficient DSP algorithm techniques such as Loop Unrolling and MAC in Java
Develop the Discrete Fourier Transform (DFT) algorithm in Java
Develop the Inverse Discrete Fourier Transform (IDFT) algorithm in Java
Develop the Fast Fourier Transform (FFT) algorithm in Java
Perform spectral analysis on ECG signals in Java
Design and develop Windowed-Sinc filters in Java
Design and develop Finite Impulse Response (FIR) filters in Java
Design and develop Infinite Impulse Response (IIR) filters in Java
Develop the Moving Average filter algorithm in Java
Develop the Recursive Moving Average filter algorithm in Java
Be able to build Bessel, Chebyshev and Butterworth filters
Understand all about Linear Systems and their characteristics
Understand how to synthesize and decompose signals
Plot signals with gnuplot
Give a lecture on Digital Signal Processing (DSP)
Suppress noise in signals

Requirements
No programming experience needed - I'll teach you everything you need to know
No paid software required - all DSP programs will be created in IntelliJ IDEA (which is free)
Description
With a programming based approach, 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. The goal of this course is to present practical techniques while avoiding obstacles of abstract mathematical theories. To achieve this goal, the DSP techniques are explained in plain language and computer code, not simply proven to be true through mathematical derivations.

Still keeping it simple, this course comes in different programming languages and hardware architectures so that students can put the techniques to practice using a programming language or hardware architecture of their choice. This version of the course uses the Java programming language.

With each dsp topic we shall develop two versions of the same algorithm. One version shall be focused on code readable and the other version shall focus on robustness and execution speed- we shall employ programming techniques such loop unrolling and Multiply- Accumulate (MAC) to accomplish this.

By the end of this course you should be able build a complete DSP library in java, develop the Convolution Kernel algorithm in Java, develop the Discrete Fourier Transform (DFT) algorithm in Java, develop the Inverse Discrete Fourier Transform (IDFT) algorithm in Java, design and develop Finite Impulse Response (FIR) filters in Java, design and develop Infinite Impulse Response (IIR) filters in Java, develop Windowed-Sinc filters in Java, build Modified Sallen-Key filters, build Bessel, Chebyshev and Butterworth filters, develop the Fast Fourier Transform (FFT) algorithm in Java, even give a lecture on DSP and so much more. Please take a look at the full course curriculum.

Who this course is for:
If you are an absolute beginner to signal processing, then take this course.
I you are already familiar with the theory of dsp then take this course to learn how to translate the mathematical equations into code
If you are a java developer take this course to learn how to build robust DSP algorithms in java

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