Auscultation is the act of listening to the sounds of internal organs. It is an effective non-invasive clinical tool to monitor the respiratory system. Since more than 200 years the stethoscope is used for auscultation. The inherent inter-listener variability and the recent technical advances yield to an increased interest in computer-aided lung sound research.
Sum-product networks (SPNs) are a recently proposed tractable probabilistic model allowing exact and efficient inference. This thesis focuses on discussing new learning paradigms for SPNs as well as integrating SPNs with recent research in Bayesian nonparameterics. In particular, I focus on the following research questions:
Many machine learning algorithms seek for a mode in a posterior distribution and then make predictions solely based on that mode. These approaches waste lots of information available in the posterior and are prone to overfitting when a bad local mode is found. The full Bayesian approach computes its prediction by an expectation over the posterior. Computing this expectation analytically is in general intractable and subject of current research. The task of the thesis is to develop techniques based on the full Bayesian approach:
It is hypothesized that the use of cognitive system concepts as well as multiple input, multiple output techniques can enable accurate and robust indoor localization using a passive radio frequency identification (RFID) system.
Linear-chain conditional random fields (LC-CRFs) have been successfully applied in many structured prediction tasks. LC-CRFs can be extended by different types of deep models.
Radar systems provide information about object distances, velocities and positions but they can also be used for object recognition, such as pedestrian classification. The constant sensing of the various sensors in a car produces a huge amount of raw data, which requires an intelligent extraction of relevant data as well as distributed processing on the sensing units themselves. In this project we investigate the use of machine learning methods such as Deep Neural Networks to address these issues. Special attention is placed on resource efficiency of the used models in order to deploy them directly to the hardware.
Systems of polynomial equations occur in many engineering problems. Finding the common roots of a system of multivariate polynomials is at the heart of various fields of mathematics.
The positioning accuracy that can be achieved using communication over a wireless link between transceivers is envisioned to be improved by the introduction of multiple antenna elements at the RF-devices.
In the upcoming years we face the reality of everyday objects being connected to a large network, the ‘Internet of Things’ (IoT). A key aspect of the IoT is dependable communication and localization, where the participants act as ‘Smart Things’, communicating with each other and being aware of their environment.
A basic assumption in room acoustics is that the sound field above the Schröder frequency in an enclosed surface is highly diffuse. But how diffuse can a sound field get? The international standard ISO 354 suggests a measurement procedure to increase the diffusivity of a sound field inside a laboratory environment by adding panel diffusers. Although the standard does not give an absolute measure for diffusivity, it defines the quality of the sound field by measuring the reverberation time and calculating the absorption coefficient of a sample. This procedure is highly questionable because it is not possible to achieve comparable accuracy between different laboratories and the absorption coefficient reaches values > 1 which is physically not possible. In this work, the hypothesis is set up that panel diffusers create coupled spaced and therefore reduce the effective volume of the chamber.
- Adaptive Calibration of Frequency Response MIsmatches in Time-Interleaved Analog-to-Digital Converters
- Adaptive Digital Predistortion of Nonlinear Systems
- Auditory Inspired Methods for Multiple Speaker Localization and Tracking Using a Circular Microphone Array
- Behavioral Modeling and Digital Predistortion of Radio Frequency Power Amplifiers
- Cognitive Indoor Positioning and Tracking using Multipath Channel Information
- Complex Baseband Modeling and Digital Predistortion for Wideband RF Power Amplifiers
- Digital Enhancement and Multirate Processing Methods for Nonlinear Mixed Signal Systems
- Diplophonic Voice: Definitions, models, and detection
- Distributed Sparse Bayesian Regression in Wireless Sensor Networks
- Efficient Floating-Point Implementation of Speech Processing Algorithms on Reconfigurable Hardware
- Enhancement for Disordered and Substitution Voices
- Improving automatic speech recognition for pluricentric languages exemplified on varieties of German
- Indoor localization using RF channel information
- Information Theory for Signal Processing
- Kernel PCA and Pre-Image Iterations for Speech Enhancemen
- Localization, Characterization, and Tracking of Harmonic Sources: With Applications to Speech Signal Processing
- Low Complexity Correction Structures for Time-Varying Systems
- Low-Complexity Localization using Standard-Compliant UWB Signals
- Low Complexity Ultra-wideband (UWB) Communication Systems in Presence of Multiple-Access Interference
- Maximum Margin Bayesian Networks
- Measurement Methods for Estimating the Error Vector Magnitude in OFDM Transceivers
- Modeling and Mitigation of Narrowband Interference for Non-Coherent UWB Systems
- Modeling, Identification, and Compensation of Channel Mismatch Errors in Time-Interleaved Analog-to-Digital Converters
- Multipath-Assisted Indoor Positioning
- Multipath Tracking and Prediction for Multiple-Input Multiple-Output Wireless Channels
- Nonlinear System Identification for Mixed Signal Processing
- Phonetic Similarity Matching of Non-Literal Transcripts in Automatic Speech Recognition
- Position Aware RFID Systems
- Probabilistic Model-Based Multiple Pitch Tracking of Speech
- Quality Aspects of Packet-Based Interactive Speech Communication
- Semantic Similarity in Automatic Speech Recognition for Meetings
- Signal Processing for Burst‐Mode RF Transmitter Architectures
- Signal Processing for Ultra Wideband Transceivers
- Signal Processing in Phase-Domain All-Digital Phase-Locked Loops
- Source-Filter Model Based Single Channel Speech Separation
- Sparse Pulsed Auditory Representations For Speech and Audio Coding
- Speech Enhancement for Disordered and Substitution Voices
- Speech Enhancement of Electro-Larynx Speech
- Speech Watermarking and Air Traffic Control
- Statistical Signal Processing of Complex-Valued Data for Speech Processing
- UWB Channel Fading Statistics and Transmitted Reference Communication
- Variable Delay Speech Communication over Packet-Switched Networks
- Wavelet Analysis For Robust Speech Processing and Applications