M. Tech. Electrical Engineering. / Applies conditional optimisation to ML decoding of perfect STBCs, it is hypothesised that the obtained algorithms have reduced complexity and exhibit high DLP and TLP that can be exploited to map them on low-power multi-core SIMD processors, and possibly to reduce their runtimes and allow their real-time execution in a 4G wireless system.

M. Tech. Mathematical Technology. / Aims of this research project is to mathematically analyse froth patterns and build a database of the images at different stages of the fermentation process, so that a decision-making procedure can be developed, which enables a computer to react according to what has been observed. This would allow around-the-clock observation which is not possible with humans. In addition, mechanised decision-making would minimize errors usually associated with human actions. Different mathematical algorithms for image processing will be considered and compared. These algorithms have been designed for different image processing situations. In this dissertation the algorithms will be applied to froth images in particular and will be used to simulate the human eye for decision-making in the fermentation process. The preamble of the study will be to consider algorithms for the detection of edges and then analyse these edges. MATLAB will be used to do the pre-processing of the images and to write and test any new algorithms designed for this project.

Indiana University-Purdue University Indianapolis (IUPUI) / Multiresolution image fusion is an emerging area of research for use in military and commercial applications. While many methods for image fusion have been developed, improvements can still be made. In many cases, image fusion methods are tailored to specific applications and are limited as a result. In order to make improvements to general image fusion, novel methods have been developed based on the wavelet transform and empirical variance. One particular novelty is the use of directional filtering in conjunction with wavelet transforms. Instead of treating the vertical, horizontal, and diagonal sub-bands of a wavelet transform the same, each sub-band is handled independently by applying custom filter windows. Results of the new methods exhibit better performance across a wide range of images highlighting different situations.

Indiana University-Purdue University Indianapolis (IUPUI) / Highway noise can cause annoyance, affect sleep patterns, and reduce the property value for people in the proximity. Current methods for analyzing the effectiveness of sound barriers only take loudness into consideration. This paper introduces new methods that can be used to analyze the effectiveness of the sound barriers. Our approach uses psychoacoustic measures including sharpness, roughness, fluctuation, strength, and annoyance. Highway noise is non-stationary, therefore each of these metrics are calculated over a short time. Finally analysis is performed the distribution and change over time. We used nth nearest neighbor algorithm to remove sounds that are not a part of the experiment. In the future, this data can be combined with human surveys to see if the change in sound quality due to the presence of sound barriers has a meaningful impact on people's lives.

Indiana University-Purdue University Indianapolis (IUPUI) / The recording and processing of bioelectric signals over the decades has led to the development of many different types of analog filtering and amplification techniques. Meanwhile, there have also been many advancements in the realm of digital signal processing that allow for more powerful analysis of these collected signals. The issues with present acquisition schemes are that (1) they introduce irreversible distortion to the signals and may ultimately hinder analyses that rely on the unique morphological differences between bioelectric signal events and (2) they do not allow the collection of frequencies in the signal from direct-current (DC) to high-frequencies. The project put forth aims to overcome these two issues and present a new scheme for bioelectric signal acquisition and processing. In this thesis, a system has been developed, verified, and validated with experimental data to demonstrate the ability to build an invertible universal amplifier and digital restoration scheme. The thesis is primarily divided into four sections which focus on (1) the introduction and background information, (2) theory and development, (3) verification implementation and testing, and (4) validation implementation and testing. The introduction and background provides pertinent information regarding bioelectric signals and recording practices for bioelectric signals. It also begins to address some of the issues with the classical and present methods for data acquisition and make the case for why an invertible universal amplifier would be better. The universal amplifier transfer function and architecture are discussed and presented along with the development and optimization of the characterization and the inversion, or restoration, filter process. The developed universal amplifier, referred to as the invertible universal amplifier (IUA), while the universal amplifier and the digital restoration scheme together are referred to as the IUA system. The IUA system is then verified on the bench using typical square, sine, and triangle waveforms with varying offsets and the results are presented and discussed. The validation is done with in-vivo experiments showing that the IUA system may be used to acquire and process bioelectric signals with percent error less than to 6% when post-processed using estimated characteristics of and when compared to a standard flat bandwidth high-pass cutoff amplifier.