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The last few years have seen the start of a unique change in microphones for consumer devices such as smartphones or tablets. Almost all analogue capacitive microphones are being replaced by digital silicon microphones or MEMS microphones. MEMS microphones perform differently to conventional analogue microphones. Their greatest disadvantage is significantly increased self-noise or decreased SNR, while their most significant benefits are ease of design and manufacturing and improved sensitivity matching. This thesis presents research on speech processing, comparing conventional analogue microphones with the newly available digital MEMS microphones. Specifically, voice activity detection, speaker diarisation (who spoke when), speech separation and speech recognition are looked at in detail. In order to carry out this research different microphone arrays were built using digital MEMS microphones and corpora were recorded to test existing algorithms and devise new ones. Some corpora that were created for the purpose of this research will be released to the public in 2013. It was found that the most commonly used VAD algorithm in current state-of-theart diarisation systems is not the best-performing one, i.e. MLP-based voice activity detection consistently outperforms the more frequently used GMM-HMM-based VAD schemes. In addition, an algorithm was derived that can determine the number of active speakers in a meeting recording given audio data from a microphone array of known geometry, leading to improved diarisation results. Finally, speech separation experiments were carried out using different post-filtering algorithms, matching or exceeding current state-of-the art results. The performance of the algorithms and methods presented in this thesis was verified by comparing their output using speech recognition tools and simple MLLR adaptation and the results are presented as word error rates, an easily comprehensible scale. To summarise, using speech recognition and speech separation experiments, this thesis demonstrates that the significantly reduced SNR of the MEMS microphone can be compensated for with well established adaptation techniques such as MLLR. MEMS microphones do not affect voice activity detection and speaker diarisation performance.

The demographic history of human populations, both archaic and modern, have been the focus of extensive research. Earlier studies were based on a small number of genetic markers but technological advances have made possible the examination of data at the genome scale to answer important questions regarding the history of our species. A widely used application of single nucleotide polymorphisms (SNPs) are genotyping arrays that allow the study of several hundred thousand of these sites at the same time. However, most of the SNPs present in commercial genotyping arrays have often been discovered by sampling a small number of chromosomes from a group of selected populations. This form of non-random discovery skews patterns of nucleotide diversity and can affect population genetic inferences. Although different methods have been proposed to take into account this ascertainment bias, the challenge remains because the exact discovery protocols are not known for most of the commercial arrays. In this dissertation, I propose a demographic inference pipeline that explicitly models the underlying SNP discovery and I implement this methodology in specific examples of admixture in human populations when only SNP array data are available. In the first chapter, I describe the developed pipeline and applied it to a known example of recent population admixture in Mexico. The inferred time of admixture between Iberian and Native American populations that gave rise to admixed Mexicans was in line with historical records, as opposed to previous published underestimates. Next, I examined different demographic models on the first human settlement in Easter Island and determined that the island of Mangareva is the most likely point of origin for this migration. Finally, I investigated the dynamics of the admixture process between the ancestral Jomon and Yayoi populations in different locations across Japan. The estimates of the time of this encounter were closer to dates inferred from anthropological data, in contrast with past works. The results show that the proposed framework corrects ascertainment bias to improve inference in cases when only SNP chip data are available, and for genotype data originated from different platforms.

Since its invention, phased array has been extensively applied in both military and civil areas. The applications include target detecting and tracking, space probe communication, broadcasting, human-machine interfaces, and remote sensing. Although the phased array applications show a broad range of potential market, there are some limitations of phased array's development: high cost, complex structure, narrow bandwidth, and high power consumption. Therefore, novel ideas are needed to reduce these constraints. In this thesis, several new approaches about the design and application of phased array are presents. First, the principle of phased array and fundamental design equations are introduced. Second, a new application of phased array antenna for radar respiration measurement is presented. By integrating a 4×4 Butler matrix with four-element antenna array, there will be four distinct main beams in radiation pattern. This new approach can improve the measurement accuracy and realize a high detecting rate. Third, a compact phased array antenna system based on dual-band operations is introduced. Dual-band function can make N-antenna system obtain 2N unique radiation beams (N is an integer) and achieve a significant size reduction compared to the conventional single-band system. To verify the design concept, a four-element phased array antenna working at 5GHz and 8GHz is designed and fabricated. The measurement results make a good agreement with the simulations. Finally, a novel architecture of steering phase feeding network by using bi-directional series-fed topology is presented. This bi-directional series-fed network needs less phase shifters and realizes steering phase function by applying control voltage.