In this thesis, we analyze the performance of the Post Detection Integration (PDI) techniques used for detection of weak DS/CDMA signals in the presence of uncertainty in the frequency, noise variance and data bits. Such weak signal detection problems arise, for example, in the first step of code acquisition for applications such as the Global Navigation Satellite Systems (GNSS) based position localization. Typically, in such applications, a combination of coherent and post-coherent integration stages are used to improve the reliability of signal detection. We show that the feasibility of using fully coherent processing is limited due to the presence of unknown data-bits and/or frequency uncertainty. We analyze the performance of the two conventional PDI techniques, namely, the Non-coherent PDI (NC-PDI) and the Differential-PDI (D-PDI), in the presence of noise and data bit uncertainty, to establish their robustness for weak signal detection. We show that the NC-PDI technique is robust to uncertainty in the data bits, but a fundamental detection limit exists due to uncertainty in the noise variance. The D-PDI technique, on the other hand, is robust to uncertainty in the noise variance, but its performance degrades in the presence of unknown data bits. We also analyze the following different variants of the NC-PDI and D-PDI techniques: Quadratic NC-PDI technique, Non-quadratic NC-PDI, D-PDI with real component (D-PDI (Real)) and D-PDI with absolute component (D-PDI (Abs)). We show that the likelihood ratio based test statistic derived in the presence of data bits is non-robust in the presence of noise uncertainty. We propose two novel PDI techniques as a solution to the above mentioned shortcomings in the conventional PDI methods. The first is a cyclostationarity based sub-optimal PDI technique, that exploits the periodicity introduced due to the data bits. We establish the exact mathematical relationship between the D-PDI and cyclostationarity-based signal detection methods. The second method we propose is a modified PDI technique, which is robust against both noise and data bit uncertainties. We derive two variants of the modified technique, which are tailored for data and pilot channels, respectively. We characterize the performance of the conventional and proposed PDI techniques in terms of their false alarm and detection probabilities and compare them through the receiver operating characteristic (ROC) curves. We derive the sample complexity of the test-statistic in order to achieve a given performance in terms of detection and false alarm probabilities in the presence of model uncertainties. We validate the theoretical results and illustrate the improved performance that can be obtained using our proposed PDI protocols through Monte-Carlo simulations.

Extracting speaker-specific information from speech is of great interest to both researchers and developers alike, since speaker recognition technology finds application in a wide range of areas, primary among them being forensics and biometric security systems. Several models and techniques have been employed to extract speaker information from the speech signal. Speech production is generally modeled as an excitation source followed by a filter. Physiologically, the source corresponds to the vocal fold vibrations and the filter corresponds to the spectrum-shaping vocal tract. Vocal tract-based features like the melfrequency cepstral coefficients (MFCCs) and linear prediction cepstral coefficients have been shown to contain speaker information. However, high speed videos of the larynx show that the vocal folds of different individuals vibrate differently. Voice source (VS)-based features have also been shown to perform well in speaker recognition tasks, thereby revealing that the VS does contain speaker information. Moreover, a combination of the vocal tract and VS-based features has been shown to give an improved performance, showing that the latter contains supplementary speaker information. In this study, the focus is on extracting speaker information from the VS. The existing techniques for the same are reviewed, and it is observed that the features which are obtained by fitting a time-domain model on the VS perform poorly than those obtained by simple transformations of the VS. Here, an attempt is made to propose an alternate way of characterizing the VS to extract speaker information, and to study the merits and shortcomings of the proposed speaker-specific features. The VS cannot be measured directly. Thus, to characterize the VS, we first need an estimate of the VS, and the integrated linear prediction residual (ILPR) extracted from the speech signal is used as the VS estimate in this study. The voice source linear prediction model, which was proposed in an earlier study to obtain the ILPR, is used in this work. It is hypothesized here that a speaker’s voice may be characterized by the relative proportions of the harmonics present in the VS. The pitch synchronous discrete cosine transform (DCT) is shown to capture these, and the gross shape of the ILPR in a few coefficients. The ILPR and hence its DCT coefficients are visually observed to distinguish between speakers. However, it is also observed that they do have intra-speaker variability, and thus it is hypothesized that the distribution of the DCT coefficients may capture speaker information, and this distribution is modeled by a Gaussian mixture model (GMM). The DCT coefficients of the ILPR (termed the DCTILPR) are directly used as a feature vector in speaker identification (SID) tasks. Issues related to the GMM, like the type of covariance matrix, are studied, and it is found that diagonal covariance matrices perform better than full covariance matrices. Thus, mixtures of Gaussians having diagonal covariances are used as speaker models, and by conducting SID experiments on three standard databases, it is found that the proposed DCTILPR features fare comparably with the existing VS-based features. It is also found that the gross shape of the VS contains most of the speaker information, and the very fine structure of the VS does not help in distinguishing speakers, and instead leads to more confusion between speakers. The major drawbacks of the DCTILPR are the session and handset variability, but they are also present in existing state-of-the-art speaker-specific VS-based features and the MFCCs, and hence seem to be common problems. There are techniques to compensate these variabilities, which need to be used when the systems using these features are deployed in an actual application. The DCTILPR is found to improve the SID accuracy of a system trained with MFCC features by 12%, indicating that the DCTILPR features capture speaker information which is missed by the MFCCs. It is also found that a combination of MFCC and DCTILPR features on a speaker verification task gives significant performance improvement in the case of short test utterances. Thus, on the whole, this study proposes an alternate way of extracting speaker information from the VS, and adds to the evidence for speaker information present in the VS.

L’engouement actuel pour les applications de type réseaux de capteurs sans-fil ou internet des objets (IoT) relance la nécessité, alors initiée par les applications mobiles, de concevoir des émetteurs-récepteurs radio à basse consommation. Dans ce contexte, l’objet des travaux de thèse est de proposer des techniques de réduction de la consommation des récepteurs radio tout en minimisant l’impact sur leur architecture de manière à pouvoir adapter leur consommation aux besoins de performance.Pour ce faire, l’utilisation intermittente du convertisseur analogique numérique (ADC) a, dans un premier temps, été étudiée puis celle-ci a été généralisée à l’ensemble du récepteur. Pour chacune de ces approches, une modélisation de la dégradation des performances en termes de taux d’erreur (BER) a été confrontée à une estimation de la réduction de la consommation engendrée. Par ailleurs, l’impact de l’ajout de modules spécifiques aux techniques proposées est décrit à l’aide de résultats concernant leurs complexités et leurs consommations. L’ensemble de ces résultats s’inscrit pleinement dans le domaine de recherche des récepteurs adaptatifs pour lesquels les performances sont adaptées au canal de transmission en temps réel.Finalement, une technique de compensation digitale des défauts de quadrature a été proposée, rendant possible l’utilisation d’une PLL moins énergivore mais avec des performances dégradées. Cette technique utilise une recherche par dichotomie des poids de compensation des défauts de quadrature, lui permettant de converger suffisamment rapidement pour pouvoir réaliser la compensation sur une portion connue du message reçu et ainsi éviter une perte d’information. / The recent craze for the Wireless Sensor Networks (WSN) and the Internet of Things (IoT) applications boosts the necessity, previously introduced by the mobile applications, to design low power transceivers. In this context, the purpose of this thesis is to propose some techniques to reduce the power consumption of RF receivers while minimizing the impact on their architecture in order to be able to adapt their power consumption to the required performances.To do so, the study of the intermittent use of the analog-to-digital converter (ADC) is firstly proposed and then extended to the whole receiver. In each case, the degradation of the receiver performances in terms of bit error rate (BER) is compared to an estimate of the obtained decrease of the power consumption. Moreover, the complexity and the overhead power consumption of the modules involved in the processing of the proposed techniques are also estimated and discussed. All these results are part of the field of research called “adaptive receiver” that tries to adapt the receiver performances to its environment in real time.Finally, a digital compensation technique of the quadrature imbalances was proposed. It allows using a less energy-consuming PLL but with degraded quadrature performances and compensating the mismatches in the digital domain. This technique uses a dichotomic search of the compensation weights allowing a fast convergence in order for the compensation to be done during the reception of a known portion of the received message and therefore avoiding a loss of information.

In this thesis, methods for radar-based environment perception from the vehicle safety point of view are presented. The proposed methods comprise advanced topics of radar-based target detection and tracking in dynamic pre-crash scenarios, as well as ghost object identification. The problem of a wandering dominant scatter point on the target surface and corresponding challenge for accurate target tracking in low-range configurations is considered. The proposed method presents a procedure to estimate target wheel positions and corresponding bulk velocities to serve as fixed scatter points on the target surface. Input to this method are raw radar data. The technique spatially resolves the micro-Doppler signals, generated by the rotating wheels of the target vehicle, to determine characteristic scatter points on the target surface. A micro-Doppler parameter is defined to quantify detections that are with high probability generated by the rotating target wheels. This group of detections is processed to estimate the wheel position and corresponding bulk velocities of the target, referred to as wheel hypotheses. The proposed method is evaluated in dynamic driving scenarios, where the driver performs an emergency evading action to avoid a collision. Subsequently, the detected wheel hypotheses serve as input to a developed tracking framework, which is used to estimate the target object static and dynamic states. Since the number of detected wheel hypotheses varies, a random-finite-set-based measurement model is used to incorporate multiple wheel hypotheses detected for one extended target object. The tracking performance is evaluated in critical evading scenarios using real vehicles as the target object. In addition, the thesis emphasized the problem of ghost object generation due to multipath propagation in pre-crash scenarios. Radar sensors, perceiving the immediate vehicle environment, show an elevated ghost object presence due to a higher probability illuminating potential reflection surfaces, e.g., road boundaries or buildings. At times, these ghost objects appear to be on a collision trajectory with the ego vehicle, whereas the vehicles are in uncritical driving scenarios, e.g., an urban intersection. In real-world driving scenarios, one target object may generate multiple false-positive targets. Based on the propagation and reflection behavior of electromagnetic waves, a geometric multipath model is derived, illustrating the occurring multipath reflections on real-world surfaces, e.g., buildings or road-bounding barriers. The proposed geometric propagation model describes the relative positions of the false-positive reflections and is validated with extensive real radar data. A custom reflector target mounted on a platform, creating deterministic point targets as dominant backscatter centers of a vehicle body, validated the different multipath reflections and the overall accuracy of the model. Moreover, radar measurements of a vehicle during an intersection scenario proved relevance to multipath reflection behavior and confirmed the model assumptions. Third, the relevance of skid scenarios with high magnitudes of side slip angles in pre-crash phases is highlighted. A novel test methodology, to non-destructively transfer vehicles with mounted surround sensors in skid situations, is developed and a survey analyzing a state-of-the-art radar sensor revealed the potential to improve object tracking performance. A test vehicle, equipped with a state-of-the-art automotive radar sensor and a reference sensor, was tested in real skid situations using a kick plate and a standardized radar target. The test method utilizes the side slip angle as a criticality criterion, which may be adjusted by the kick plate. Subsequently, a novel, modified motion model is derived, estimating side slip angles in these skid driving situations. The contribution emphasizes the estimation of horizontal vehicle motion using the proposed model considering an additional lateral force applied to the vehicle rear axle. Based on these results, an Extended-Kalman filter is designed to estimate the target object relative position and velocity in skid scenarios. The evaluation includes both the tracking and side slip angle estimations in real car tests using the above-mentioned test method.

In the present work, the magnetotransport measurement technique was developed and various materials, exhibiting resistances from 1 mOhm up to several tens of kOhm, were investigated in pulsed magnetic fields of up to 60 T. Phase diagrams of irreversibility and upper critical fields for pure and Zn-doped YBa2Cu3O_7-x high-temperature superconductors were measured. A high-field study of the electronic properties of the two semimetals LaBiPt and CeBiPt were presented. Magnetoresistance of La0.7Sr0.3MnO3 and La0.7Ca0.3MnO3 thin films were investigated.

This diploma thesis deals with methods of the onset and tempo detection in audio signals using specific techniques of digital processing. It analyzes and describes the issue from both the musical and the technical side. First, several implementations using different programming environments are tested. The system with the highest detection accuracy and adjustable parameters is selected, which is then used to test functionality on the reference database. Then, an extension of the algorithm based on the Teager-Kaiser energy operator in the preprocessing stage is created. The difference in accuracy of both systems is compared – the operator has on average increased the accuracy of detection of a global tempo and inter-beat intervals. Finally, a second dataset containing 33 different interpretations of the first movement of Bedřich Smetana’s composition, String Quartet No. 1 in E minor "From My Life". The results show that the average tempo of the entire first movement of the song slightly decreases depending on the later year of the recording.

The aim of this thesis is to design a connection of the development kit for the subscriber line interface circuit Si3220 with the development kit for the digital signal processor DSP56858EVM and implement a test application, which will allow us to use the development kit as a small private branch exchange. The application allows us to operate up to ten telephone machines and it disposes of basic telephone exchange functions -- generating tones to the headphone, detecting the DTMF dialing, generating the ringing and the voice connection of the subscribers.

This work deals with digital signal processing in the field of adaptive filtering. Fundamental basics of adaptive filtering are described and primary aim is to create executable laboratory examples, using adaptive filtering, in LabView programming language. These laboratory examples are intended to be used by students fo studying and during laboratory lessons. Objective is to connect the examples with external devices, such as microphone. A microphone is used as an user's speech input acquiring interface. In the thesis is depicted Wiener's filter and problem of adaptive filtering is discussed. Contemporary adaptive algorithms are described and their applications as well. Most mentioned is the LMS algorithm and it's forms. Laboratory examples use following concepts: Adaptive Echo Cancellation, Active Noise Control and System Identification. Each of these examples is solely executable (need for LabView or Run-time engine), consisting also of theory with diagrams. Examples therefore are usable even without manual.

This master’s thesis deals with the issue of digital to analog conversion and possibility of its realization in digital circuits. Goal of this project is to design sigma-delta digital to analog converter with resolution of 14 bits and frequency band (0 ÷ 20) kHz. Main functional blocks: interpolator and modulator sigma-delta will be realized like digital structures. Reconstruction filter will be realized like an analog structure. For design a check of parameters of designed converter programs MATLAB and Simulink are used. Designed digital structures will be described by VHDL language.

V systému s kódy zbytkových tříd je základem skupina navzájem nezávislých bází. Číslo ve formátu integer je reprezentováno kratšími čísly integer, které získáme jako zbytky všech bází, a aritmetické operace probíhají samostatně na každé bázi. Při aritmetických operacích nedochází k přenosu do vyšších řádů při sčítání, odečítání a násobení, které obvykle potřebují více strojového času. Srovnávání, dělení a operace se zlomky jsou komplikované a chybí efektivní algoritmy. Kódy zbytkových tříd se proto nepoužívají k numerickým výpočtům, ale jsou velmi užitečné pro digitální zpracování signálu. Disertační práce se týká návrhu, simulace a mikropočítačové implementace funkčních bloků pro digitální zpracování signálu. Funkční bloky, které byly studovány jsou nově navržené konvertory z binarní do reziduální reprezentace a naopak, reziduální sčítačka a násobička. Nově byly také navržené obslužné algoritmy.