Lectures
1. Introduction to audio and image signal processing in control and industrial systems.
2. Sound acquisition and digitization using microphones and ADC for industrial applications.
3. Frequency analysis of audio signals using DFT, FFT, and spectrogram methods.
4. Synthesis and generation of audio signals using modulation.
5. Speech signal analysis using MFCC, LPC, and classical recognition methods.
6. AI methods for audio processing using neural networks.
7. Acquisition and digitization of image signals in industrial camera systems.
8. Image data preprocessing using filters for noise removal and normalization.
9. Geometric and brightness transformations of images, including histogram methods.
10. Image frequency analysis using 2D FFT and frequency domain filters.
11. Convolutional methods for edge detection and morphological operations in machine vision.
12. Image segmentation and object detection methods for control and automation.
13. AI methods for object recognition and advanced methods in industry.
Labs
1. Measurement and processing of audio and image data using MATLAB, Python, and virtual instrumentation.
2. Implementation and digitization of sound using ADC and DAC in MATLAB, Python, and a microcontroller.
3. Preprocessing of audio signals using filters and noise removal methods.
4. Audio analysis using frequency methods in MATLAB and Python.
5. Generation and synthesis of audio signals using digital methods.
6. Audio signal feature extraction using signal recognition methods.
7. Implementation of AI models for sound and speech classification in Python.
8. Measurement and processing of image data from camera systems using MATLAB, Python, and virtual instruments.
9. Image preprocessing and filtration for machine vision.
10. Geometric and brightness image transformations, including histogram adjustments.
11. Image frequency analysis using 2D FFT and frequency filters.
12. Implementation of edge detection and morphological operations in MATLAB, Python, and a microcontroller.
13. Image segmentation and implementation of object recognition methods using artificial intelligence.
1. Introduction to audio and image signal processing in control and industrial systems.
2. Sound acquisition and digitization using microphones and ADC for industrial applications.
3. Frequency analysis of audio signals using DFT, FFT, and spectrogram methods.
4. Synthesis and generation of audio signals using modulation.
5. Speech signal analysis using MFCC, LPC, and classical recognition methods.
6. AI methods for audio processing using neural networks.
7. Acquisition and digitization of image signals in industrial camera systems.
8. Image data preprocessing using filters for noise removal and normalization.
9. Geometric and brightness transformations of images, including histogram methods.
10. Image frequency analysis using 2D FFT and frequency domain filters.
11. Convolutional methods for edge detection and morphological operations in machine vision.
12. Image segmentation and object detection methods for control and automation.
13. AI methods for object recognition and advanced methods in industry.
Labs
1. Measurement and processing of audio and image data using MATLAB, Python, and virtual instrumentation.
2. Implementation and digitization of sound using ADC and DAC in MATLAB, Python, and a microcontroller.
3. Preprocessing of audio signals using filters and noise removal methods.
4. Audio analysis using frequency methods in MATLAB and Python.
5. Generation and synthesis of audio signals using digital methods.
6. Audio signal feature extraction using signal recognition methods.
7. Implementation of AI models for sound and speech classification in Python.
8. Measurement and processing of image data from camera systems using MATLAB, Python, and virtual instruments.
9. Image preprocessing and filtration for machine vision.
10. Geometric and brightness image transformations, including histogram adjustments.
11. Image frequency analysis using 2D FFT and frequency filters.
12. Implementation of edge detection and morphological operations in MATLAB, Python, and a microcontroller.
13. Image segmentation and implementation of object recognition methods using artificial intelligence.