Signal processing problems, solved in MATLAB and in Python Download
Application-oriented instruction in signal processing and digital signal processing (DSP) using MATLAB and Python code
What you will learn
- Understanding commonly used signal processing tools
- Design, evaluate, and apply a digital filter
- Clean and denoise Data
- Know what to look for when something goes wrong with the data or code
- Increase MATLAB or Python programming skills
- Know how to generate test signals for the signal processing method
- * Fully manually corrected English captions!
- basic programming experience in MATLAB or Python
- high school math
Why do you need to learn digital signal processing?
Nature is mysterious, beautiful, and complex. Trying to understand nature is very useful, but also in challenging. One of the major challenges in the study of nature is the analysis of the data. Nature likes to mix different sources and many sources of noise signals into the same record, and it makes you work harder.
Great idea DSP (digital signal processing) is to discover the mysteries hidden in the time series data, and this course will teach you the most common strategy used the invention.
What is special about this course?
The main focus of this program is the implementation of signal processing techniques in MATLAB and Python. Some theories and equations that show, but I’m guessing you are reading this because you want to apply DSP techniques on real signals, not just polish the abstract theory.
This course is equipped with more than 10,000 lines of MATLAB and Python code, plus a set of data samples that you can use to learn and to adapt to your own course or applications.
In this course, you’ll also learn how to simulate signals to test and learn more about the processing and analysis of your signal method.
Are there any prerequisites?
You need some programming experience. I went through the video in MATLAB, and you can also follow along using the Octave (the free, cross-platform program that emulates MATLAB). I provide the appropriate Python code if you prefer Python. You may use other languages, but you will need to do the translation yourself.
I recommend taking the Fourier Transform me just before or along with this course. However, this is not a requirement, and you can succeed in this course without taking any Fourier transform.
What should you do now?
Watch a sample video, and check out my other review courses – many of them are “best-seller” or “top-rated” and has a lot of positive reviews. If you are unsure whether the program is right for you, then do not hesitate to send me a message. I hope you see you in class!
Who this course is for:
- Students in signal processing or digital signal
- scientific or industrial researchers who analyze data
- Developers working with time-series data
- Someone who wants to refresh their knowledge of screening
- Engineers who studied mathematics from DSP and want to learn about the implementation of the software
Created by Mike X Cohen