The purpose of this thesis is to describe novel signal processing methodologies and analog integrated circuit techniques for low-power biomedical systems. Physiological signals, such as the electrocardiogram (ECG), the electroencephalogram (EEG) and the electromyogram (EMG) are mostly non-stationary. The main difficulty in dealing with biomedical signal processing is that the information of interest is often a combination of features that are well localized temporally (e.g., spikes) and others that are more diffuse (e.g., small oscillations). This requires the use of analysis methods sufficiently versatile to handle events that can be at opposite extremes in terms of their time-frequency localization. Wavelet Transform (WT) has been extensively used in biomedical signal processing, mainly due to the versatility of the wavelet tools. The WT has been shown to be a very efficient tool for local analysis of nonstationary and fast transient signals due ...

The aim of this dissertation is the investigation of the key issues encountered in the development of wideband radio air-interfaces. Orthogonal frequency-division multiplexing (OFDM) is considered as the enabling technology for transmitting data at extremely high rates over time-dispersive radio channels. OFDM is a transmission scheme, which splits up the data stream, sending the data symbols simultaneously at a drastically reduced symbol rate over a set of parallel sub-carriers. The first part of this thesis deals with the modeling of the time-dispersive and frequency-selective radio channel, utilizing second order Gaussian stochastic processes. A novel channel measurement technique is developed, in which the RMS delay spread of the channel is estimated from the level-crossing rate of the frequency-selective channel transfer function. This method enables the empirical channel characterization utilizing simplified non-coherent measurements of the received power versus frequency. Air-interface and multiple ...

The increasing number of simultaneous input and output channels utilized in immersive audio configurations primarily in broadcasting applications has renewed industrial requirements for efficient audio coding schemes with low bit-rate and complexity. This thesis presents a comprehensive review and extension of conventional approaches for perceptual coding of arbitrary multichannel audio signals. Particular emphasis is given to use cases ranging from two-channel stereophonic to six-channel 5.1-surround setups with or without the application-specific constraint of low algorithmic coding latency. Conventional perceptual audio codecs share six common algorithmic components, all of which are examined extensively in this thesis. The first is a signal-adaptive filterbank, constructed using instances of the real-valued modified discrete cosine transform (MDCT), to obtain spectral representations of successive portions of the incoming discrete time signal. Within this MDCT spectral domain, various intra- and inter-channel optimizations, most of which are of ...

The multi-frequency Global Navigation Satellite System (GNSS) signals are designed to overcome the inherent performance limitations of single-frequency receivers. However, the processing of multiple frequency signals in a time-varying GNSS signal environment which are potentially affected by multipath, ionosphere scintillation, blockage, and interference is quite challenging, as each signal is influenced differently by channel effects according to its Radio Frequency (RF). In order to get the benefit of synchronously/coherently generated multiple frequency signals, advanced receiver signal processing techniques need to be developed. The aim of this research thesis is to extract the best performance benefits out of multifrequency GNSS signals in a time-varying GNSS signal environment. To accomplish this objective, it is necessary to analyze the multi-frequency signal characteristics and to investigate suitable signal processing algorithms in order to enable the best performance of each signal. The GNSS receiver position ...

The number of cameras increases rapidly in squares, shopping centers, railway stations and airport halls. There are hundreds of cameras in the city center of Amsterdam. This is still modest compared to the tens of thousands of cameras in London, where citizens are expected to be filmed by more than three hundred cameras of over thirty separate Closed Circuit Television (CCTV) systems in a single day [84]. These CCTV systems include both publicly owned systems (railway stations, squares, airports) and privately owned systems (shops, banks, hotels). The main purpose of all these cameras is to detect, prevent and monitor crime and anti-social behaviour. Other goals of camera surveillance can be detection of unauthorized access, improvement of service, fire safety, etc. Since the terrorist attack on 9/11, detection and prevention of terrorist activities especially at high profiled locations such as airports, ...

Radio resource allocation in communication networks is essential to achieve optimal performance and resource utilization. In modern interference networks the corresponding optimization problems are often nonconvex and their solution requires significant computational resources. Hence, practical systems usually use algorithms with no or only weak optimality guarantees for complexity reasons. Nevertheless, asserting the quality of these methods requires the knowledge of the globally optimal solution. State-of-the-art global optimization approaches mostly employ Tuy's monotonic optimization framework which has some major drawbacks, especially when dealing with fractional objectives or complicated feasible sets. In this thesis, two novel global optimization frameworks are developed. The first is based on the successive incumbent transcending (SIT) scheme to avoid numerical problems with complicated feasible sets. It inherently differentiates between convex and nonconvex variables, preserving the low computational complexity in the number of convex variables without the need ...

This work has, as its objective, the development of non-invasive and low-cost systems for monitoring and automatic diagnosing specific neonatal diseases by means of the analysis of suitable video signals. We focus on monitoring infants potentially at risk of diseases characterized by the presence or absence of rhythmic movements of one or more body parts. Seizures and respiratory diseases are specifically considered, but the approach is general. Seizures are defined as sudden neurological and behavioural alterations. They are age-dependent phenomena and the most common sign of central nervous system dysfunction. Neonatal seizures have onset within the 28th day of life in newborns at term and within the 44th week of conceptional age in preterm infants. Their main causes are hypoxic-ischaemic encephalopathy, intracranial haemorrhage, and sepsis. Studies indicate an incidence rate of neonatal seizures of 2‰ live births, 11‰ for preterm ...

Cellular Neural Networks are characterized by simplicity of operation. The network consists of a large number of nonlinear processing units; called cells; that are equally spread in the space. Each cell has a simple function (sequence of multiply-add followed by a single discrimination) that takes an element of a topographic map and then interacts with all cells within a specified sphere of interest through direct connections. Due to their intrinsic parallel computing power, CNNs have attracted the attention of a wide variety of scientists in, e.g., the fields of image and video processing, robotics and higher brain functions. Simplicity of operation together with the local connectivity gives CNNs first-hand advantages for tiled VLSI implementations with very high speed and complexity. The first VLSI implementation has been based on analogue technology but was small and suffered from parasitic capacitances and resistances ...

Multisensor systems are a key enabling technology in, e.g., radar, sonar, medical ultrasound, and wireless communications. Using multiple sensors provides spatial selectivity, improves the signal-to-noise ratio, and enables rejecting unwanted interference. Conventional multisensor systems employ a simple array of uniformly spaced sensors with a linear or rectangular geometry. However, a uniform array spanning a large electrical aperture may become prohibitively expensive, as many sensors and costly RF-IF front ends are needed. In contrast, sparse sensor arrays require drastically fewer resources to achieve comparable performance in terms of spatial resolution and the number of identifiable scatterers or sources. This is facilitated by the co-array: a virtual array structure consisting of the pairwise differences or sums of physical sensor positions. Most recent works on co-array-based sparse array design focus exclusively on passive sensing. Active sensing, where sensors transmit signals and observe their ...

To enable ultra-high data rate and ubiquitous coverage in future wireless networks, new physical layer techniques are desired. Relaying is a promising technique for future wireless networks since it can boost the coverage and can provide low cost wireless backhauling solutions, as compared to traditional wired backhauling solutions via fiber and copper. Traditional one-way relaying (OWR) techniques suffer from the spectral loss due to the half-duplex (HD) operation at the relay. On one hand, two-way relaying (TWR) allows the communication partners to transmit to and/or receive from the relay simultaneously and thus uses the spectrum more efficiently than OWR. Therefore, we study two-way relays and more specifically multi-pair/multi-user TWR systems with amplify-and-forward (AF) relays. These scenarios suffer from inter-pair or inter-user interference. To deal with the interference, advanced signal processing algorithms, in other words, spatial division multiple access (SDMA) techniques, ...

Given the widespread use of miniaturized audio interfaces, echo control systems are faced with increasing challenges to address a large variety of acoustic conditions observed by such interfaces. This motivates the use of sophisticated machine learning-based techniques to overcome the limitations of conventional methods. The contributions in this thesis can be outlined by decomposing the task of nonlinear acoustic echo control into two subtasks: Nonlinear Acoustic Echo Cancellation (NAEC) and Acoustic Echo Suppression (AES). In particular, by formulating the single-channel NAEC model-adaptation task as a Bayesian recursive filtering problem, an evolutionary resampling strategy for particle filtering is proposed. The resulting Elitist Resampling Particle Filter (ERPF) is shown experimentally to be an efficient and high-performing approach that can be extended to address challenging conditions such as non-stationary interferers. The fundamental problem of nonlinear model design is addressed by proposing a novel ...

Nowadays, energy efficiency (EE) for wireless communications is becoming a main economical and societal challenge. This thesis studies resource allocation (RA) in EE optimized wireless communication systems for various system models. The main body of this thesis consists of three parts. In the first part, EE optimization is studied in multiple input multiple output (MIMO)-orthogonal frequency-division multiplexing (OFDM) systems. Two special scenarios are considered respectively in two chapters: rate-dependent circuit power and nonlinear distortion at the high power amplifier (HPA). For the first scenario, the condition of the rate-dependent circuit power such that the global optimal EE is guaranteed to be found is given. The impact of system parameters on EE are analyzed. For the second scenario, the condition of parameters of HPA such that the rate function is concave is given. In the second part, EE maximized subcarrier allocation ...

Since their inception, energy dissipation has been a critical issue for mobile computing systems. Although a large research investment in low-energy circuit design and hardware level energy management has led to more energy-efficient architectures, even then, there is a growing realization that the contribution to energy conservation should be more rigorously considered at higher levels of the systems, such as operating systems and applications. This dissertation puts forth the claim that energy-aware compilation to improve appli- cation quality both in terms of execution time and energy consumption is essential for a high performance mobile computing embedded system design. Our work is a design paradigm shift from the logic gate being the basic silicon computation unit, to an in- struction running on an embedded processor. Multimedia DSP processors are the most lucrative choice to a mobile computing system design for their ...

Using a hearing device is one of the most successful approaches to partially restore the degraded functionality of an impaired auditory system. However, due to the complex structure of the human auditory system, hearing impairment can manifest itself in different ways and, therefore, its compensation can be achieved through different classes of hearing devices. Although the majority of hearing devices consists of conventional hearing aids (HAs), several other classes of hearing devices have been developed. For instance, bone-conduction devices (BCDs) and cochlear implants (CIs) have successfully been used for more than thirty years. More recently, other classes of implantable devices have been developed such as middle ear implants (MEIs), implantable BCDs, and direct acoustic cochlear implants (DACIs). Most of these different classes of hearing devices rely on a sound processor running different algorithms able to compensate for the hearing impairment. ...

Wireless sensor networks has been one of the major research topics in recent years because of its great potential for a wide range of applications. In some application scenarios, sensor nodes intend to report the sensing data to a far-field destination, which cannot be realized by traditional transmission techniques. Due to the energy limitations and the hardware constraints of sensor nodes, distributed transmit beamforming is considered as an attractive candidate for long-range communications in such scenarios as it can reduce energy requirement of each sen-sor node and extend the communication range. However, unlike conventional beamforming, which is performed by a centralized antenna array, distributed beamforming is performed by a virtual antenna array composed of randomly located sensor nodes, each of which has an independent oscillator. Sensor nodes have to coordinate with each other and adjust their transmitting signals to collaboratively ...