Professor Mark Sandler, BSc PhD FREng CEng FIEEE FAES FIET

Teaching

Digital Signal Processing (Undergraduate)

This is a Level 6 module, which builds upon the signal processing theory introduced in ELE374, Signals and Systems Theory. The main part of the module covers the theory of digital signal processing techniques and digital filter design. The module concludes with an examination of some applications of digital signal processing.

Fundamentals of DSP (Postgraduate/Undergraduate)

Introduction: Why DSP, sampling, quantization, Signals, LTI systems, Z transforms and polynomials, DFT, FFT, Spectrum Analysis, FIR filters, IIR filters

Research

Research Interests:

Digital Signal Processing, Machine Learning and Deep Learning especially for Audio and Music. Topics include: Digital Music & Digital Audio; Audio Segmentation; Harmonic Analysis; Source Separation; Neural Audio; Audio Synthesis; Physics-informed Neural Networks.

In the past I have done research in many areas in audio and music. These include: fractal and chaotic audio modelling, digital audio power amplification, sigma-delta modulation (SDM) for Digital to Analogue Conversion (DACs), immersive and surround sound (including ambisonic to binaural conversion, perceptual evaluation), high order all-pole modelling of musical instruments, drum synthesis, efficient architectures for EQ, music recommendation and play listing, key and chord analysis, vocal imitation for browsing of sound sample collections, linked data for music informatics and music cultural heritage.

I also spent around 10 years working in Computer Vision. Topics included several multi-processor architectures for high throughput processing, edge detection and thinning, Hough Transform for parametric detection of curves and lines in images, optical flow techniques.

Publications