<p>In hands-free telephony and in teleconference systems, the main aim is to provide agood free voice quality when two or more people communicate from different places.The problem often arises during the conversation is the creation of acoustic echo. Thisproblem will cause the bad quality of voice signal and thus talkers could not hearclearly the content of the conversation, even thought lost the important information.This acoustic echo is actually the noise which is created by the reflection of soundwaves by the wall of the room and the other things exist in the room. The mainobjective for engineers is the cancellation of this acoustic echo and provides an echofree environment for speakers during conversation. For this purpose, scientists designdifferent adaptive filter algorithms. Our thesis is also to study and simulate theacoustics echo cancellation by using different adaptive algorithms.</p>

<p>Death from heart diseases is the most common type of mortality in western countries and the survival rate of cardiac arrest is dismally low. In the treatment of cardiac arrest, two therapeutic methods are most important: cardiopulmonary resuscitation (CPR; chest compressions and ventilations) and defibrillation (electrical shocks to restart a fibrillating heart).</p><p>An automated external defibrillator is commonly used for such shocks, and records and performs signal analysis on the electrocardiogram(ECG) in order to advice when to shock the patient. However, the mechanical activity during CPR introduces artifact components in the ECG. To perform reliable ECG signal analysis, CPR is therefore discontinued for a substantial time before the potential delivery of a shock. This wastes valuable therapy time, and if this hands-off time could be reduced or eliminated by removing these artifacts, it should improve the chance of return of spontaneous circulation.</p><p>We propose a method for removing CPR artifacts using a novel multichannel adaptive filter, the computationally efficient and numerically robust MultiChannel Recursive Adaptive Matching Pursuit(MC-RAMP) filter. Using the most realistic data set to date, human out-of-hospital cardiac arrest data of both shockable and non-shockable rhythms, we test MC-RAMP and evaluate the feasibility of ECG analysis during CPR. In our experiments we use a shock advice algorithm and individual ECG signal features to reach the conclusion that after CPR artifact filtering, ECG rhythm analysis during ongoing CPR is feasible. </p><p>Finally, we analyze and quantify the time intervals without blood flow (no flow time(NFT)) during external automatic defibrillation in cardiac arrest patients and show that these patients were not perfused around half of the time. We propose methods using CPR artifact filtering to reduce the NFT, and show their significant and promising potential. By introducing the proposed methods into defibrillators, the NFT would be significantly reduced, hopefully increasing the survival.</p>

Death from heart diseases is the most common type of mortality in western countries and the survival rate of cardiac arrest is dismally low. In the treatment of cardiac arrest, two therapeutic methods are most important: cardiopulmonary resuscitation (CPR; chest compressions and ventilations) and defibrillation (electrical shocks to restart a fibrillating heart). An automated external defibrillator is commonly used for such shocks, and records and performs signal analysis on the electrocardiogram(ECG) in order to advice when to shock the patient. However, the mechanical activity during CPR introduces artifact components in the ECG. To perform reliable ECG signal analysis, CPR is therefore discontinued for a substantial time before the potential delivery of a shock. This wastes valuable therapy time, and if this hands-off time could be reduced or eliminated by removing these artifacts, it should improve the chance of return of spontaneous circulation. We propose a method for removing CPR artifacts using a novel multichannel adaptive filter, the computationally efficient and numerically robust MultiChannel Recursive Adaptive Matching Pursuit(MC-RAMP) filter. Using the most realistic data set to date, human out-of-hospital cardiac arrest data of both shockable and non-shockable rhythms, we test MC-RAMP and evaluate the feasibility of ECG analysis during CPR. In our experiments we use a shock advice algorithm and individual ECG signal features to reach the conclusion that after CPR artifact filtering, ECG rhythm analysis during ongoing CPR is feasible. Finally, we analyze and quantify the time intervals without blood flow (no flow time(NFT)) during external automatic defibrillation in cardiac arrest patients and show that these patients were not perfused around half of the time. We propose methods using CPR artifact filtering to reduce the NFT, and show their significant and promising potential. By introducing the proposed methods into defibrillators, the NFT would be significantly reduced, hopefully increasing the survival.

Orthogonal frequency division multiplexing (OFDM) technique has been extensively used in digital wireless communications, such as Digital Broadcasting and wireless local area network (WLAN). It is considered to be one of the most promising techniques for transmission on the downlinks of broadband wireless access systems to combat multipath and multiple access interference (MAI). Spatial processing that exploits the diversity provided by smart antenna (SA) or intelligent antenna (IA) arrays, in which the adaptive beamformer is employed, is another alternatives to increase the efficiency of wireless system capacity and performance without allocating additional frequency spectrum. It allows the system to make full use of spatial diversity due to multiple antennas [5][6]. To further improve the performance for suppressing various interference sources; including narrowband and wideband interference, flat and frequency selective fading, for different channel environmentin. In this thesis, a smart antenna with wideband beamspace approach array beamformer associated with the slideing window (SW) linearly constrained RLS (SW-LC-RLS) algorithm, and the OFDM systems with smart antenna array are emhasized. Computer simulation results confirmed that our proposed scheme could achieve desired performance compared with the conventional approach, in terms of MAI and other interference suppression.

Spatial processing that exploits the diversity provided by smart antenna arrays, in which the adaptive beamformer is employed, is another alternative to increase the efficiency of wireless system capacity and performance without allocating additional frequency spectrum. An array beamformer is a processor used in conjunction with an array of sensors to provide a versatile form of spatial filtering; it can be designed to form main lobe in direction corresponding to the desired source and nulling the interferences from others direction. They are two types of adaptive array beamformer structures, viz., broadband and narrowband array structures. To deal with the wideband desired signal or interferences the broadband array beamformer is preferred. For broadband interferences suppression, many adaptive array beamforming algorithms, based on the linearly constrained have been extensively used. In this thesis, the beamspace approach for designing the broadband antenna array beamformer, with frequency invariant character, is devised and implemented with the sliding window linearly constrained RLS (SW-LC-RLS) algorithm, to deal with the broadband moving jammers (or interferences) suppression. Also, to combat the pointing error effect of desired user¡¦s look direction, the derivative constraint is adopted for devising the derivative SW-LC-RLS beamforming algorithm for broadband moving jammers suppression. Computer simulation results confirmed that the proposed scheme is more robust against the moving jammers over the conventional algorithms. It can be applied to the existing wideband wireless communications systems to achieve desired performance for supporting high data rate communication services.

n the problem of time delay estimation (TDE), the desired source signals of interest are correlated and with a specific spectral distribution. In such cases, the convergence speed using the conventional approaches, viz., time domain adaptive constrained and unconstrained LMS TDE algorithms, becomes slowly and the performance of TDE will be degraded, dramatically. In fact, the convergence rate depends highly on the distribution of spectral density of the desired signal sources. Also, the performance of TDE is affected by the background noises, accordingly. To circumvent the problem described above, in this thesis, a transformed domain adaptive constrained filtering scheme, refers to the constrained adaptive DCT-LMS algorithm, for TDE is devised. We show that this new proposed constrained algorithm, with the so-called direct delay estimation formula, for non-integer TDE does perform better than the conventional time domain adaptive constrained and unconstrained LMS TDE algorithms and the unconstrained adaptive DCT-LMS TDE algorithm. Finally, to further reduce the spread of eigenvalue in the unconstrained adaptive DCT-LMS algorithm, the Gram-Schmidt orthogonalizer approach realizing by the adaptive Escalator is investigated. It indicates that bias of TDE will occur without using the constraint of weight vector. That is, it could not be used to alleviate the effect due to background noises.

The convergence speed using the conventional approaches, viz., time-domain adaptive constrained and unconstrained LMS algorithms, becomes slowly, when dealing with the correlated source signals. In consequence, the performance of time delay estimation (TDE) will be degraded, dramatically. To improve this problem, the so-called transform-domain adaptive constrained filtering scheme, i.e., the adaptive constrained discrete-cosine-transform (DCT) LMS algorithm, has been proposed in [15]. However, the use of any one orthogonal transform will not result in a completely diagonal the input signal auto-correlation matrix for all types of input signals. In fact, the significant non-diagonal entries in the transform-domain auto-correlation matrix, will deteriorate the convergence performance of the algorithm. To further overcome the problem described above, in this thesis, a modified approach, referred as the adaptive constrained modified DCT-LMS (CMDCT-LMS) algorithm, is devised for TDE under a wide class of input processes. In addition, based on the orthogonal discrete wavelet transform (DWT), an adaptive constrained modified DMT-LMS (CMDWT-LMS) algorithm is also devised and applied to the problem of TDE. We show that the proposed two modified constrained approaches for TDE does perform well than the unmodified approaches under different source signal models. Moreover, the adaptive CMDCT-LMS filtering algorithm does perform slightly better than the adaptive CMDWT-LMS filtering algorithm as observed from the simulation results.

There has been much effort in new design for transceiver used in mobile communications. The general approach is to combine RF functions with DSP to allow linear modulation techniques and permit flexibility of modulation format and receiver processing. In practice, with the quadrature modulation technique there is always some imbalance between the I- and Q channels of modulator and demodulator. This is mainly due to finite tolerances of capacitor and resistor values used to implement the analog components. The unavoidable imbalance between the I- and Q channels is known to degrade the performance of quadrature communication system. The main concern of this thesis is to propose a new blind scheme and with fast convergence algorithm, such as the inverse QRD-RLS algorithm, to deal with the problem described above for compensation in the transmitter and receiver. First, for the transmitter, the so-called adaptive estimation and compensation with power measurement implemented by the inverse QRD-RLS algorithm is employed. While in the receiver, a new blind adaptive filtering approach of the nonlinear parameters estimation and compensation, along with the power measurement in the receiver, is devised to adaptively compensate for the gain/phase imbalance and DC offsets in a quadrature demodulator. Where the conventional inverse QRD-RLS algorithm is employed for estimating the parameters of compensator, without using any reference signal transmitted from the transmitter. To document the merits of the proposed scheme, computer simulation for the coherent 16-PSK-communication system is carried out. With our proposed method a great improvement for eliminating the effects of the imbalance and offset over the existing techniques has verified. It has rapidly convergence rate and the smaller mean square error in steady state.

The technique of direct sequence code division multiple access (DS-CDMA) cellular system has been the focus of increased attention. In this thesis, we will consider the environment of DS-CDMA systems, where the asynchronous narrow band interference due to other systems is joined suddenly to the CDMA system. The suddenly joined narrow band interference will make the system crush down. The main concern of this thesis is to deal with suddenly joined narrow band interference cancellation. An adaptive filtering algorithm based on sliding window criterion and variable forgetting factor is known to be very attractive for violent changing environment. In this thesis, a new sliding window linearly constrained recursive least squares (SW LC-RLS) algorithm and variable forgetting factor linearly constrained recursive least squares (VFF LC-RLS) algorithm on the modified minimum mean squared error (MMSE) structure [9] is devised for RAKE receiver in direct sequence code-division multiple access (DS-CDMA) system over multipath fading channels. Where the channel estimation scheme is accomplished at the output of adaptive filter. The proposed SW LC-RLS algorithm and VFF LC-RLS has the advantage of having faster convergence property and tracking ability, and can be applied to the environment, where the narrow band interference is suddenly joined to the system, to achieve desired performance. Via computer simulation, we show that the performance, in terms of mean square errors (MSE) and signal to interference plus noise ratio (SINR), is superior to the conventional LC-RLS and orthogonal decomposition-based LMS algorithms based on the MMSE structure [9].

Στην παρούσα διπλωματική εργασία ασχοληθήκαμε με τον μη επεμβατικό προσδιορισμό του κορεσμού οξυγόνου στο αίμα με τη χρήση παλμικού οξύμετρου (ή πιο απλά σφυγμοξύμετρου) και ειδικότερα με την αφαίρεση θορύβου από το πληθυσμιογραφικό σήμα του. Αρχικά, γίνεται μια εισαγωγή στη βιοϊατρική τεχνολογία, στις εφαρμογές και τις υπηρεσίες που αυτή παρέχει στον τομέα της υγείας στον 21ο αιώνα έτσι ώστε να καταστεί σαφής η χρησιμότητα της βιοϊατρικής τεχνολογίας σε ευρύτατους τομείς της ζωής μας. Στη συνέχεια γίνεται μια πρώτη γνωριμία με το σφυγμοξύμετρο εισάγοντας έννοιες και μαθηματικούς νόμους που περιγράφουν τις γενικές αρχές σχεδίασής του. Έπειτα, παραθέτουμε αναλυτικά όλα τα είδη θορύβου τα οποία μπορούν να θέσουν την ακρίβεια των μετρήσεων του σφυγμοξύμετρου υπό αίρεση καθώς και μια πληθώρα απλών και σύνθετων μεθόδων για την αφαίρεση θορύβου και τον ακριβή προσδιορισμό του κορεσμού οξυγόνου. Τέλος, παρουσιάζεται αναλυτικά ο προσαρμοστικός ακυρωτής θορύβου που προτείνεται από την εταιρεία Masimo Corporation αλλά και η υπολογιστική μέθοδος καθορισμού της τιμής του κορεσμού οξυγόνου που προτείνεται από την εταιρεία Texas Instruments. Τα ανωτέρω υλοποιούνται σε ένα ενιαίο υπολογιστικό πρόγραμμα σε γλώσσα προγραμματισμού C που εκτελεί προσαρμοστική ακύρωση θορύβου και υπολογίζει τον κορεσμό οξυγόνου και το οποίο εφαρμόζεται σε πέντε διαφορετικά σετ μετρούμενων σημάτων σφυγμοξύμετρου. / -