<p>The next generation satellite communication networks will provide multimedia services supporting high bit rate, mobility, ATM, and TCP/IP. In these cases, the satellite technology will act as the internetwork infrastructure of future global systems and assuming a global wireless system, no distinctions will exist between terrestrial and satellite communications systems, as well as between fixed and 3G mobile networks. In order for satellites to be successful, they must handle bursty traffic from users and provide services compatible with existing ISDN infrastructure, narrowcasting/multicasting services not offered by terrestrial ISDN, TCP/IP-compatible services for data applications, and point-to-point or point-to-multipoint on-demand compressed video services. This calls for onboard processing payloads capable of frequency multiplexing and demultiplexing and interference suppression.</p><p>This thesis introduces a new class of oversampled complex modulated filter banks capable of providing frequency multiplexing and demultiplexing. Under certain system constraints, the system can handle all possible shifts of different user signals and provide variable bandwidths to users. Furthermore, the aliasing signals are attenuated by the stopband attenuation of the channel filter thus ensuring the approximation of the perfect reconstruction property as close as desired. Study of the system efficient implementation and its mathematical representation shows that the proposed system has superiority over the existing approaches for Bentpipe payloads from the flexibility, complexity, and perfect reconstruction points of view. The system is analyzed in both SISO and MIMO cases. For the MIMO case, two different scenarios for frequency multiplexing and demultiplexing are discussed.</p><p>To verify the results of the mathematical analysis, simulation results for SISO, two scenarios of MIMO, and effects of the finite word length on the system performance are illustrated. Simulation results show that the system can perform frequency multiplexing and demultiplexing and the stopband attenuation of the prototype filter controls the aliasing signals since the filter coefficients resolution plays the major role on the system performance. Hence, the system can approximate perfect reconstruction property by proper choice of resolution.</p>

In order to understand the migration patterns of migrating birds, it is necessary to understand whenand where to they migrate. Many of these birds are very small and thus cannot carry heavy sensors;hence it is necessary to be able to perform positioning using a very small sensor. One way to do this isto use a light-intensity sensor. Since the sunrise and sunset times are known given time and position onthe earth, it is possible to determine the global position using light intensity. Light intensity increasesas the sun rises. Data sets from several calibration sensors, mainly from different locations in Sweden, have been examinedin different ways in order to get an understanding of the measurements and what affects them. Inorder to perform positioning, it is necessary to know the solar elevation angle, which can be computedif the time and position are known, as is the case for the calibration sensors. This has been utilized toidentify a mapping from measured light intensity to solar elevation angle, which is used to computepseudo-measurements for target tracking, described below. In this thesis, positioning is performed using methods from the field of target tracking. This is doneboth causally (filtering) and non-causally (smoothing). There are certain problems that arise; firstly,the measured light intensity can be attenuated due to weather conditions such as cloudiness, which ismodelled as a time-varying offset. Secondly, the sensor can be shadowed causing outliers in the data.Furthermore, birds are not always in a migratory state, they oftentimes stay in one place. The lattertwo phenomena are modelled using an Interacting Multiple Model (IMM) where they are representedas discrete states, corresponding to different models.

The next generation satellite communication networks will provide multimedia services supporting high bit rate, mobility, ATM, and TCP/IP. In these cases, the satellite technology will act as the internetwork infrastructure of future global systems and assuming a global wireless system, no distinctions will exist between terrestrial and satellite communications systems, as well as between fixed and 3G mobile networks. In order for satellites to be successful, they must handle bursty traffic from users and provide services compatible with existing ISDN infrastructure, narrowcasting/multicasting services not offered by terrestrial ISDN, TCP/IP-compatible services for data applications, and point-to-point or point-to-multipoint on-demand compressed video services. This calls for onboard processing payloads capable of frequency multiplexing and demultiplexing and interference suppression. This thesis introduces a new class of oversampled complex modulated filter banks capable of providing frequency multiplexing and demultiplexing. Under certain system constraints, the system can handle all possible shifts of different user signals and provide variable bandwidths to users. Furthermore, the aliasing signals are attenuated by the stopband attenuation of the channel filter thus ensuring the approximation of the perfect reconstruction property as close as desired. Study of the system efficient implementation and its mathematical representation shows that the proposed system has superiority over the existing approaches for Bentpipe payloads from the flexibility, complexity, and perfect reconstruction points of view. The system is analyzed in both SISO and MIMO cases. For the MIMO case, two different scenarios for frequency multiplexing and demultiplexing are discussed. To verify the results of the mathematical analysis, simulation results for SISO, two scenarios of MIMO, and effects of the finite word length on the system performance are illustrated. Simulation results show that the system can perform frequency multiplexing and demultiplexing and the stopband attenuation of the prototype filter controls the aliasing signals since the filter coefficients resolution plays the major role on the system performance. Hence, the system can approximate perfect reconstruction property by proper choice of resolution.

This thesis studies the application of the wavelet filter bank (WFB) in perceptual audio coding by providing brief overviews of perceptual coding, psychoacoustics, wavelet theory, and existing wavelet coding algorithms. Furthermore, it describes the poor frequency localization property of the WFB and explores one filter design method, in particular, for improving channel separation between the wavelet bands. A wavelet audio coder has also been developed by the author to test the new filters. Preliminary tests indicate that the new filters provide some improvement over other wavelet filters when coding audio signals that are stationary-like and contain only a few harmonic components, and similar results for other types of audio signals that contain many spectral and temporal components. It has been found that the WFB provides a flexible decomposition scheme through the choice of the tree structure and basis filter, but at the cost of poor localization properties. This flexibility can be a benefit in the context of audio coding but the poor localization properties represent a drawback. Determining ways to fully utilize this flexibility, while minimizing the effects of poor time-frequency localization, is an area that is still very much open for research.

Transform-domain (TD) sampling is seen as a potential candidate for wideband and ultra-wideband high-performance receivers and is investigated in detail in this research. TD receivers expand the signal over a set of basis functions and operate on the digitized basis coefficients. This parallel digital signal processing relaxes the sampling requirements opening the doors to higher dynamic range and wider bandwidth in receivers. This research is focused on the implementation of a high performance multi-channel wideband receiver that is based on Frequency-domain (FD) sampling, a special case of TD sampling. To achieve high dynamic ranges in these receivers, it is critical that the digital post processing block matches the analog RF front end accurately. This accurate matching has to be ensured across several process variations, mismatches and o�sets that can be present in integrated circuit implementations. A unified model has been defined for the FD multi-channel receiver that contains all these imperfections and a joint synchronization and calibration technique, based on the Least-mean-squared (LMS) algorithm, is presented to track them. A maximum likelihood (ML) algorithm is used to estimate the frequency offset in carriers which is corrected prior to LMS calibration. Simulation results are provided to support these concepts. The sampling circuits in FD receivers are based on charge-sampling and a multi-channel charge-sampling receiver creates an inherent sinc filter-bank that has several advantages compared to the conventional analog filter banks used in other multi-channel receivers. It is shown that the sinc filter banks, besides reduced analog complexity, have very low computational complexity in data estimation which greatly reduces the digital power consumption of these filters. The digital complexity of data estimation in the sinc fiter bank is shown to be less than 1=10th of the complexity in analog filter banks.

Hearing impairment is the number one chronic disability affecting people in the world. Many people have great difficulty in understanding speech with background noise. This is especially true for a large number of elderly people and the sensorineural impaired persons. Several investigations on speech intelligibility have demonstrated that subjects with sensorineural loss may need a 5-15 dB higher signal-to-noise ratio than the normal hearing subjects. While most defects in transmission chain up to cochlea can nowadays be successfully rehabilitated by means of surgery, the great majority of the remaining inoperable cases are sensorineural hearing impaired, Recent statistics of the hearing impaired patients applying for a hearing aid reveal that 20% of the cases are due to conductive losses, more than 50% are due to sensorineural losses, and the rest 30% of the cases are of mixed origin. Presenting speech to the hearing impaired in an intelligible form remains a major challenge in hearing-aid research today. Even-though various methods have been suggested in the literature for the minimization of noise from the contaminated speech signals, they fail to give good SNR improvement and intelligibility improvement for moderate to-severe sensorineural loss subjects. So far, the power and capability of Newton's method, Nonlinear adaptive filtering methods and the feedback type artificial neural networks have not been exploited for this purpose. Hence we resort to the application of all these methods for improving SNR and intelligibility for the sensorineural loss subjects. Digital hearing aids frequently employ the concept of filter banks. One of the major drawbacks of this techniques is the complexity of computation requiring more number of multiplications. This increases the power consumption. Therefore this Thesis presents the new approach to speech enhancement for the hearing impaired and also the construction of filter bank in Digital hearing aid with minimum number of multiplications. The following are covered in this thesis. One of the most important application of adaptive systems is in noise cancellation using adaptive filters. The ANC setup requires two input signals (viz., primary and reference). The primary input consists of the sum of the desired signal and noise which is uncorrelated. The reference input consists of mother noise which is correlated in Some unknown way with noise of primary input. The primary signal is obtained by placing the omnidirectional microphone just above one ear on the head of the KEMAR mannikan and the reference signal is obtained by placing the hypercardioid microphone at the center of the vertebral column on the back. Conventional speech enhancement techniques use linear schemes for enhancing speech signals. So far Nonlinear adaptive filtering techniques are not used in hearing aid applications. The motivation behind the use of nonlinear model is that it gives better noise suppression as compared to linear model. This is because the medium through which signals reach the microphone may be highly nonlinear. Hence the use of linear schemes, though motivated by computational simplicity and mathematical tractability, may be suboptimal. Hence, we propose the use of nonlinear models to enhance the speech signals for the hearing impaired: We propose both Linear LMS and Nonlinear second order Volterra LMS schemes to enhance speech signals. Studies conducted for different environmental noise including babble, cafeteria and low frequency noise show that the second-order Volterra LMS performs better compared to linear LMS algorithm. We use measures such as signal-to-noise ratio (SNR), time plots, and intelligibility tests for performance comparison. We also propose an ANC scheme which uses Newton's method to enhance speech signals. The main problem associated with LMS based ANC is that their convergence is slow and hence their performance becomes poor for hearing aid applications. The reason for choosing Newton's method is that they have high performance adaptive-filtering methods that often converge and track faster than LMS method. We propose two models to enhance speech signals: one is conventional linear model and the other is a nonlinear model using a second order Volterra function. Development of Newton's type algorithm for linear mdel results in familiar Recursive least square (RLS) algorithm. The performance of both linear and non-linear Newton's algorithm is evaluated for babble, cafeteria and frequency noise. SNR, timeplots and intelligibility tests are used for performance comparison. The results show that Newton's method using Volterra nonlinearity performs better than RLS method. ln addition to the ANC based schemes, we also develop speech enhancement for the hearing impaired by using the feedback type neural network (FBNN). The main reason is that here we have parallel algorithm which can be implemented directly in hardware. We translate the speech enhancement problem into a neural network (NN) framework by forming an appropriate energy function. We propose both linear and nonlinear FBNN for enhancing the speech signals. Simulated studies on different environmental noise reveal that the FBNN using the Volterra nonlinearity is superior to linear FBNN in enhancing speech signals. We use SNR, time plots, and intelligibility tests for performance comparison. The design of an effective hearing aid is a challenging problem for sensorineural hearing impaired people. For persons with sensorineural losses it is necessary that the frequency response should be optimally fitted into their residual auditory area. Digital filter enhances the performance of the hearing aids which are either difficult or impossible to realize using analog techniques. The major problem in digital hearing aid is that of reducing power consumption. Multiplication is one of the most power consuming operation in digital filtering. Hence a serious effort has been made to design filter bank with minimum number of multiplications, there by minimizing the power consumption. It is achieved by using Interpolated and complementary FIR filters. This method gives significant savings in the number of arithmetic operations. The Thesis is concluded by summarizing the results of analysis, and suggesting scope for further investigation

<p>In today’s heavy industry there are applications demanding high power supply in certain periods of a working cycle. A typical case might be startup of heavy machinery or just keeping a certain point in a distribution network at a certain energy level. To deal with this different techniques might be used, one way is to introduce a battery as an energy reserve in the system. One battery studied at ABB for this purpose is the so called High Temperature Sodium Nickel Chloride battery and a model of this battery has been developed at ABB. When operating a battery of the mentioned type in an application it is important to keep track of the energy stored in the battery. Earlier tests has shown that this is difficult in a noisy environment.</p><p>This master thesis investigates if a Kalman filter may be used to estimate the energy stored in the battery. The investigation is performed in steps, starting with a simplified model of the battery and then expanding to a more complete model. Evaluation of the methods and algorithms used is made by simulations and based on the assumption that there is a good model available. The model is special in such a way that it has a varying number of states despite that the number of outputs remains the same.</p><p>Some comparisons with actual measurements are also made and an analysis of the parameters in the model along with an introduction to the system identification problem is discussed, assuming that the structure of the model is correct.</p> / <p>I dagens tunga industri finns applikationer som kräver höga effektuttag under vissa perioder av en arbetscykel. Ett typiskt fall kan vara uppstart av tunga maskiner eller att hålla en given spänningsnivå i en belastningspunkt i ett distributionsnät. För att hantera detta finns olika metoder, en möjlighet är att använda ett batteri som en energireserv. Ett högtemperaturbatteri har studerats på ABB för detta ändamål och en model av detta batteri har tagits fram. När ett sådant batteri används är det viktigt att kontinuerligt veta hur mycket energi som finns till förfogande i batteriet. Tidigare tester har visat att detta är svårt i en brusig miljö.</p><p>I detta examensarbete kommer det undersökas om ett Kalman filter kan användas för att skatta energin i detta batteri. Undersökningen sker i steg och startar med en förenklad modell som sedan utvecklas till en mer komplett modell. Utvärdering av de metoder och algoritmer som används sker via simuleringar och baseras på antagandet att modellen är komplett och riktig. Denna modell är speciell på det sätt att den har ett variabelt antal tillstånd trots att antalet utsignaler är konstant.</p><p>Viss jämförelse med de mätningar som finns tillgängliga görs och en inledande analys av de ingående modellparametrarna presenteras. Även en introduktion till det omfattande systemidentifieringsproblemet diskuteras, med antagandet att modellens struktur är korrekt.</p>

Manual sleep scoring, executed by visual inspection of the EEG, is a very time consuming activity, with an inherent subjective decisional component. Automatic sleep scoring could ease the job of the technicians, because faster and more accurate. Frequency information characterizing the main brain rhythms, and consequently the sleep stages, needs to be extracted from the EEG data. The approach used in this study involves a wavelet filter bank for the EEG frequency features extraction. The wavelet packet analysis tool in MATLAB has been employed and the frequency information subsequently used for the automatic sleep scoring by means of an artificial neural network. Finally, the automatic sleep scoring has been employed for epoching the fMRI data, thus allowing for studying brain resting state networks during sleep. Three resting state networks have been inspected; the Default Mode Network, The Attentional Network and the Salience Network. The networks functional connectivity variations have been inspected in both healthy and narcoleptic subjects. Narcolepsy is a neurobiological disorder characterized by an excessive daytime sleepiness, whose aetiology may be linked to a loss of neurons in the hypothalamic region.

In today’s heavy industry there are applications demanding high power supply in certain periods of a working cycle. A typical case might be startup of heavy machinery or just keeping a certain point in a distribution network at a certain energy level. To deal with this different techniques might be used, one way is to introduce a battery as an energy reserve in the system. One battery studied at ABB for this purpose is the so called High Temperature Sodium Nickel Chloride battery and a model of this battery has been developed at ABB. When operating a battery of the mentioned type in an application it is important to keep track of the energy stored in the battery. Earlier tests has shown that this is difficult in a noisy environment. This master thesis investigates if a Kalman filter may be used to estimate the energy stored in the battery. The investigation is performed in steps, starting with a simplified model of the battery and then expanding to a more complete model. Evaluation of the methods and algorithms used is made by simulations and based on the assumption that there is a good model available. The model is special in such a way that it has a varying number of states despite that the number of outputs remains the same. Some comparisons with actual measurements are also made and an analysis of the parameters in the model along with an introduction to the system identification problem is discussed, assuming that the structure of the model is correct. / I dagens tunga industri finns applikationer som kräver höga effektuttag under vissa perioder av en arbetscykel. Ett typiskt fall kan vara uppstart av tunga maskiner eller att hålla en given spänningsnivå i en belastningspunkt i ett distributionsnät. För att hantera detta finns olika metoder, en möjlighet är att använda ett batteri som en energireserv. Ett högtemperaturbatteri har studerats på ABB för detta ändamål och en model av detta batteri har tagits fram. När ett sådant batteri används är det viktigt att kontinuerligt veta hur mycket energi som finns till förfogande i batteriet. Tidigare tester har visat att detta är svårt i en brusig miljö. I detta examensarbete kommer det undersökas om ett Kalman filter kan användas för att skatta energin i detta batteri. Undersökningen sker i steg och startar med en förenklad modell som sedan utvecklas till en mer komplett modell. Utvärdering av de metoder och algoritmer som används sker via simuleringar och baseras på antagandet att modellen är komplett och riktig. Denna modell är speciell på det sätt att den har ett variabelt antal tillstånd trots att antalet utsignaler är konstant. Viss jämförelse med de mätningar som finns tillgängliga görs och en inledande analys av de ingående modellparametrarna presenteras. Även en introduktion till det omfattande systemidentifieringsproblemet diskuteras, med antagandet att modellens struktur är korrekt.

Quincunx filter banks are two-dimensional, two-channel, nonseparable filter banks. They are widely used in many signal processing applications. In this thesis, we study the design and applications of quincunx filter banks in the processing of two-dimensional digital signals. Symmetric extension algorithms for quincunx filter banks are proposed. In the one-dimensional case,symmetric extension is a commonly used technique to build nonexpansive transforms of finite-length sequences. We show how this technique can be extended to the nonseparable quincunx case. We consider three types of quadrantally-symmetric linear-phase quincunx filter banks, and for each of these types we show how nonexpansive transforms of two-dimensional sequences defined on arbitrary rectangular regions can be constructed. New optimization-based techniques are proposed for the design of high-performance quincunx filter banks for the application of image coding. The new methods yield linear-phase perfect-reconstruction systems with high coding gain, good analysis/synthesis filter frequency responses, and certain prescribed vanishing moment properties. We present examples of filter banks designed with these techniques and demonstrate their efficiency for image coding relative to existing filter banks. The best filter banks in our design examples outperformother previously proposed quincunx filter banks in approximately 80% cases and sometimes even outperform the well-known 9/7 filter bank from the JPEG-2000 standard.