The increased use of personal communication devices, personal computers and wireless cellular telephones enables the development of new inter-personal communication systems. The merge between computers and telephony technologies brings up the demand for convenient hands-free communications. In such systems the users wish to lead a conversation in much the same way as in a normal person-to-person conversation. The advantages of hands-free telephones are safety, convenience and greater flexibility. In many countries and regions, hand held telephony in cars is prohibited by legislation. By placing the microphone far away from the user a number of disadvantages are introduced, which results in substantial speech distortion and poor sound quality. These disturbances are mainly caused by room reverberation and background noise. Furthermore, acoustic feedback generated at the near-end side is a problem for the far-end side talker, who will hear his/her own voice echoed with 100-200 ms delay, making speech conversation substantially more difficult. Digital filtering may be used to obtain a similar sound quality as for hand held telephony. Three major tasks must be addressed in order to improve the quality of hands-free communication systems; noise suppression, room reverberation suppression, and acoustic feedback cancellation of the hands-free loudspeaker. The filtering operation must perform the above mentioned tasks without causing severe near-end speech distortion. A properly designed broad-band microphone array is able to perform all the given tasks, i.e. speech enhancement, echo cancellation and reverberation suppression, in a concise and effective manner. This is due to the fact that the spatial domain may be utilized as well as the temporal domain. This thesis deals with the problem of specification and design of beamformers used to extract the source signal information. A new subband adaptive beamforming algorithm is proposed, where many of the drawbacks embedded in conventional adaptive beamforming are eliminated. Evaluation in a car hands-free situation show the benefits of the proposed method. Blind signal separation is discussed and a new structure based on frequency domain inverse channel identification and time domain separation, is proposed. Further, filter-bank properties and design are discussed together with performance limitations in subband beamforming structures. / Avhandlingen behandlar specifikation och konstruktion av mikrofon-arrayer för att extrahera talinformation. En ny adaptiv delbands beamforming-algoritm föreslås där många av nackdelarna hos konventionella adaptiva beamformers är eliminerade. En utvärdering i en bil med ett frihands-system bekräftar fördelarna med den föreslagna metoden. Blind signal-separation diskuteras och en ny struktur föreslås, baserad på en inverterande kanalidentifiering utförd i frekvensdomän med en kontinuerlig separation utförd i tidsdomän. Filterbanks-egenskaper och designmetoder diskuteras tillsammans med begränsningar som finns i beamforming-strukturer utförda i delband.

Vehicle stability is an important consideration in vehicle design. When driver intervention is insufficient, safety can be improved by the addition of vehicle stability control (VSC). Typical vehicle stability controllers are designed using a linearized vehicle model and an assumed set of parameters. However, some parameters like mass and inertial properties may not be constant between operations. To recover controller performance in the presence of unknown parameters, adaptive estimates can be developed. This thesis seeks to implement a model reference adaptive controller for yaw rate and side slip control and to evaluate any implementation issues that may arise. A linearized vehicle model is used for controller design via a Lyapunov approach and a combined front wheel steering (FWS) and direct yaw control (DYC) controller is developed. The combined FWS+DYC controller is tested in a low friction double lane change with initial parameter estimation error. The FWS+DYC controller was found to be robust to parameter changes, and the adaptive parameter estimates did not provide any noticeable improvement over the non-adaptive case. A four wheel steering (4WS) controller is developed by a similar approach and tested under the same conditions. Both controllers were found to be effective at stabilizing the vehicle. An unexpected finding was that though the combined FWS+DYC controller was effective even in low friction conditions with parameter errors, the required motor torque was very large and oscillated rapidly. This was diminished through the addition of a low pass filter on the controller yaw moment output, but could not be removed entirely. / text

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The basal ganglia are a dynamic neural network of telencephalic subcortical nuclei, involved in adaptive control of behaviour. There has been much experimental evidence on the anatomy and physiology of the basal ganglia published over the last 25 years showing that the basal ganglia are involved in the learning of many adaptive behaviours, including motor planning, working memory and cognitive functions. Current qualitative basal ganglia models of the box and arrow type, whilst explaining much of the anatomical data, do not give enough insight into the mechanisms involved in basal ganglia function either in health or in disease states. The striatum is the main input nucleus of the basal ganglia, integrating widespread cortical and thalamic inputs to perform behaviour selection. Convergent data from control theory learning models and experimental data have shown that the phasic dopamine signal in the striatum could be performing a similar function to a scalar teaching signal in reinforcement learning models, both signals indicating the occurrence of reward. Similarly, both models and electrophysiological data have shown how the timing of this reward signal can be changed during learning so as to occur at the point in time of the earliest predictor of forthcoming reward. These models do not, however, show how this teaching signal is used in the striatum to learn to select the action most likely to lead to reward. Computational models have been produced to investigate the circuitry involved in striatal action selection. These models have tended to be of winner-takes-all networks, using a mechanism of recurrent lateral inhibition between the medium spiny cells of the striatum to select the winner and thus releasing the behavioural action judged to be correct in the current environmental context. However, the necessary biological circuitry to implement a winner-takes-all network is absent in the striatum. This leads to a requirement for new models of striatal function incorporating current biological data to provide a more realistic mechanism for behavioural selection. This thesis develops a biophysically inspired, minimal current model of a striatal medium spiny neuron which utilises transitions between two membrane potential states, both below firing threshold, to filter excitatory input. The behaviour of the model is first validated against experimental electrophysiological data and then used to demonstrate how the striatum could perform two of the tasks required for behaviour selection; accurately timed release of behaviours and learning a sequence of action selections to obtain reward. In the first series of simulations timed release of behaviours is demonstrated to be linearly related to the timing of firing of feed forward inhibitory interneurons. In a second set of simulations learned sequences of action selection, using a simulated dopamine reward signal, are shown in a reward location task performed by a small network of model medium spiny striatal neurons. Taken together these studies show that this simple model of a striatal medium spiny neuron is capable of simulating the basic functionality required for behaviour selection in a manner which has greater biological plausibility than previously published models.

Voice over IP (VoIP) is the group of techniques for delivering voice communications over Internet Protocol (IP) networks. It has mainly served as the possible substitution for regular PSTN over the last decades, but has recently gained an increased interest in various areas such as alarm applications and customer service. Acoustic echo is the situation were a distorted version of the sent signal is transmitted back to the sender, due to acoustic feedback between loudspeaker and microphone. There already exists several algorithms to solve this problem, and this thesis provides a study of the performance in relation to the computational complexity of the algorithms. This is in order to indicate which approaches are better suited for implementation in an embedded system, where resources are limited. During the thesis a number of algorithms were tested, including variations of the LMS algorithm, some other approaches utilizing the correlation between echo and signal, and the RLS algorithm. They were first tested in MATLAB, on speech signals recorded at Syntronic and distorted by adding echo, then tested by implementation in C, and run on speech signals recorded in a simulated VoIP system at Syntronic. The results were then evaluated in terms of efficiency and computational complexity.

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