Recent years have brought many new developments in the processing of speech and acoustic signals. Yet, despite this, the process of acquiring signals has gone largely unchanged. Adding spatial diversity to the repertoire of signal acquisition has long been known to offer advantages for processing signals further. The processing capabilities of mobile devices had not previously been able to handle the required computation to handle these previous streams of information. But current processing capabilities are such that the extra workload introduced by the addition of mutiple sensors on a mobile device are not over-burdensome. How these extra data streams can best be handled is still an open question. The present work deals with the examination of one type of spatial processing technique, known as beamforming. A microphone array test platform is constructed and verified through a number of beamforming agorithms. Issues related to speech acquisition through microphones arrays are discussed. The algorithms used for verification are presented in detail and compared to one another.

The estimation of the frequency and phase of a complex exponential in additive white Gaussian noise (AWGN) is a fundamental and well-studied problem in signal processing and communications. A variety of approaches to this problem, distinguished primarily by estimation accuracy, computational complexity, and processing latency, have been developed. One class of approaches is based on the Fast Fourier Transform (FFT) due to its connections with the maximum likelihood estimator (MLE) of frequency. This thesis compares several FFT-based approaches to the MLE in terms of their estimation accuracy and computational complexity. While FFT-based frequency estimation tends to be very accurate, the computational complexity of the FFT and the latency associated with performing these computations after the entire signal has been received can be prohibitive in some scenarios. Another class of approaches that addresses some of these shortcomings is based on linear regression of samples of the instantaneous phase of the observation. Linear- regression-based techniques have been shown to be very accurate at moderate to high signal to noise ratios and have the additional benefit of low computational complexity and low latency due to the fact that the processing can be performed as the samples arrive. These techniques, however, typically require the computation of four-quadrant arctangents, which must be approximated to retain low computational complexity. This thesis proposes a new frequency and phase estimator based on simple estimates of the zero-crossing times of the observation. An advantage of this approach is that it does not require arctangent calculations. Simulation results show that the zero-crossing frequency and phase estimator can provide high estimation accuracy, low computational complexity, and low processing latency, making it suitable for real-time applications. Accordingly, this thesis also presents a real-time implementation of the zero-crossing frequency and phase estimator in the context of a time-slotted round-trip carrier synchronization system for distributed beamforming. The experimental results show this approach can outperform a Phase Locked Loop (PLL) implementation of the same distributed beamforming system.

The electrocardiograph (ECG) is a common clinical and biomedical research tool used for both diagnostic and prognostic purposes. In recent years computer aided analysis of the ECG has enabled cardiographic patterns to be found which were hitherto not apparent. Many of these analyses rely upon the segmentation of the ECG into separate time delimited waveforms. The instants delimiting these segments are called the

This work deals with computer simulation of a guitar combo. The complete simulation is divided into separate blocks and then transfer characteristics and frequency responses of each block are obtained from a circuit analysis of analogue prototype. After their aproximation, the transfer characteristics are implemented as waveshapers and frequency responses are simulated using digital filters designed according to their analogue prototypes. Designed algorithms are implemented as plug-in mudule in language C++.

This work deals with a computer simulation of an acoustic room using its impulse response. Two different approaches to the simulation are described with their pros and cons and then the work is focused on the physical approach, which uses room’s impulse response during the simulation. Several methods for the extraction of the impulse response of the acoustic room are mentioned with their conditions of use. The detailed description of various algorithms for a real time convolution computing is followed by the cost analysis of frequency domain block convolution algorithms. Several algorithms are chosen, implemented and tested in Matlab environment. Then the most effective of them is chosen to be implemented in VST technology as the plug in module for real time room simulation.

Master’s thesis deals with the generation of digital audio signals with band-limited frequency spectrum, i.e. without the aliasing distortion. Various methods of generating band-limited rectangular, triangular, and sawtooth waveforms are described in the theoretical part. The described methods are programmed in the Matlab programming environment and compared in terms of real-time parameter changes, such as duty cycle change of rectangular waveform or continuous change of frequency. The main part of the thesis describes implementation of methods of successive integration of band-limited impulse train and method of differentiated parabolic waveforms in C++ language. The implemented methods were integrated into a plug-in of VST technology that generates an audio signal in real time. The implemented methods are compared in terms of computational complexity and distortion of the generated signal.