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What you would learn in DSP From Ground Up™ on ARM Processors [UPDATED] course?
Are you looking to master the art of digitization and signal processing (DSP) without confusion?
Here's a summary of what you'll learn in this DSP course on Arm processors...
Understanding the fundamentals of signal processing without complication:
Before developing DSP algorithms in practice beginning from scratch, this class will teach you the fundamental process of processing signals step by step. We will explore critical areas of signal processing such as:
Signal stats and Noise
quantization, in addition to the sampling theorem
Analog filter design
Performance indicators from these filters Chebyshev, Butterworth as well as the Bessel filters
Linear Systems and the properties they possess.
FIR stands for Finite Impulse Response Filters ( FIR)
Infinite Impulse Response Filters ( IIR)
Superposition, synthesis, and decomposition.
Convolution and its properties the phenomenon of convolution and the properties it has
The Discrete Fourier Transformation ( DFT) and IDFT
The process of developing Digital Signal Processing Algorithms:
Then we will implement the algorithms for processing signals discussed in our theory classes. Instead of using live signals, we will utilize previously recorded and created signals to evaluate our algorithm to emphasize developing methods and testing instead of acquiring signals.
We will develop these algorithms.
Signal statistical algorithms include signal mean, standard deviation, and variance.
The Convolution algorithm
The Sum Running Sum algorithm
The Discrete Fourier Transform (DFT) algorithm
The Inverse Discrete Fourier Transform ( IDFT) algorithm
We will also implement the algorithms we have developed using CMSIS-DSP. CMSIS-DSP library, and then evaluate our algorithms' effectiveness with the algorithms provided in CMSIS-DSP.
Development of Data Structures, Drivers and Drivers to Signal Acquisition
To adequately capture signals from outside the world and apply our algorithms for processing signals, we must first develop analog-to-digital converter (ADC) drivers to capture the signals and appropriate data structures for storing and managing the signals. Here we will develop the following:
A Bare-Metal ADC driver to receive the signal
A first-in,-first-out data structure used for storing and controlling the signal
Designs for Digital Filters and Implementation:
We will learn about the different kinds of digital filters available before we create the filters from beginning to finish. We will implement the following:
The Moving Average Filter
The filter is known as the Finite Impulse Reaction (FIR) filter
The Infinite Impulse Response (IIR) Filter
We will also explore how to develop for the filters Kernel for the filters with finite impulse responses by using Matlab.
A Practical DSP Application for Live Signal
Here, we'll use all our knowledge to process live signals from the microcontroller's ADC.
Course Content:
- Create efficient DSP algorithms with MAC as well as SIMD instructions
- Create RealTime Digital Signal Processing firmware
- Learn Cortex-M4, Optimization strategies for M7's DSP
- Learn to master the CMSIS-DSP Library
- Create and test and test the Convolution Kernel algorithm on ARM Processors
- Convolution is performed with a convolution using the ARM CMSIS-DSP Library.
- Test and develop The Discrete Fourier Transform (DFT) algorithm on ARM Processors
- Create and test and test the Inverse Discrete Fourier Transform (IDFT) algorithm on ARM Processors
- Create and test The Fast Fourier Transform (FFT) algorithm on ARM Processors
- Use the CMSIS-DSP Library to perform the Fast Fourier Transform (FFT). With the CMSIS-DSP Library
- Perform spectral analysis of ECG signals ARM Processors
- Create Windowed-Sinc filtering on the ARM Processors
- Develop Finite Impulse Response (FIR) filters on ARM Processors
- Develop Infinite Impulse Response (IIR) filters on ARM Processors
- Configure Finite Impulse Response (FIR) filters by using the CMSIS-DSP Library
- Configure infinite Impulse Response (FIR) filters by using the CMSIS-DSP Library
- Create passive High-pass and Low-pass filters.
- Modified Sallen - Key filters
- Develop Bessel, Chebyshev, and Butterworth filters
- Reduce the noise in signals
- Present a talk regarding Digital Signal Processing (DSP)
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