Signalbehandlings

Signalbehandlings is the study and practice of analyzing, modifying, and synthesizing signals to obtain useful information, enhance quality, or enable efficient transmission. It encompasses a wide range of signals, including audio, image, video, sensor data, and biological measurements, across communications, automation, media, and science.

Core activities include preprocessing (noise reduction, normalization), transformation and representation (time-domain, frequency-domain, time-frequency methods such as Fourier transform and wavelets), filtering (FIR, IIR), and system analysis (impulse response, convolution, transfer functions).

Digital signal processing (DSP) uses discrete-time signals and algorithms implemented on computers or specialized hardware; analog signal processing handles continuous signals with circuits. Key topics include sampling and quantization (Nyquist criterion, aliasing), discrete transforms, filtering design, spectral analysis, and compression.

Applications span telecommunications (modulation, equalization), audio processing (denoising, compression), image and video enhancement, biomedical signal analysis (ECG, EEG), radar and sonar, and instrumentation. The field supports both foundational theory and practical implementations, from designing stable filters to developing real-time processing systems.

Research areas include adaptive filtering, beamforming, machine learning for signals, and real-time processing. Challenges include nonstationary signals, noise and distortion, and computational constraints, especially in embedded or portable devices.