Digital Signal Processing (DSP) Training in Copenhagen, Denmark

This course introduces participants to Digital Signal Processing (DSP) using open-source tools like Python (NumPy, SciPy, Matplotlib, librosa) and GNU Octave. It covers signal representation, transforms, filtering, and real-world DSP applications in audio, biomedical signals, and communications.

DSP Basics & Signal Representation

• Introduction to DSP in the real world (audio, IoT, biomedical, comms)

• Discrete-time signals & sampling (Nyquist theorem, aliasing)

• Quantization and digital representation

• Convolution and linear systems

Frequency Domain Analysis

• Discrete Fourier Transform (DFT) concepts

• Fast Fourier Transform (FFT) implementation

• Spectrum analysis and filtering basics

• Power Spectral Density (PSD) using SciPy

Filter Design & Applications

• FIR filter design with windowing methods (scipy.signal)

• IIR filter design and stability analysis

• Applications in audio denoising, biomedical signal filtering, and communications

• Case study

Hands-on Exercises

Summary and Conclusion