This dissertation deals with wireless communications using cooperating relay nodes. Specifically, this dissertation relaxes two restrictive conditions ubiquitous in the current literature. First, the assumption that relay nodes can perform complex calculations is lifted. Demodulate-encode-forward (DEF) is a low-complexity relaying scheme where the relay is asked only to demodulate, not decode, a source transmission. The implementation of DEF and various methods that can be used with DEF to improve the performance while satisfying the hardware complexity limitations are detailed here. Second, we remove the assumption that the relays either transmit the complete source codeword or not transmit at all. When relays have limited resources, each relay may only be able to transmit part of the source codeword. Fractional cooperation, which allows nodes to transmit a fraction of the source codeword, is proposed and analyzed. Fractional cooperation is also very flexible because coordination between relaying nodes is not required. A third contribution of this dissertation is the use of the union-Bhattacharyya bound (UBB) to analyze relay networks. The bound has the significant advantage of accounting for the specifics of the system parameters and coding scheme used. The UBB is shown here to provide an effective and efficient scheme for relay selection, performance prediction, and system design. It can also be used to distribute relay resources in order to optimize the total energy consumed and error rate performance. A sub-optimal distributed algorithm that can be used to solve the optimization problems is introduced.

Combined coding with modulation is an important topic. It is verified in this thesis that a combined decoder and demodulation Viterbi receiver has a better error probability than a cascade of two separate Viterbi decoder and demodulator. Conventionally, the free distance is taken as the principle criterion for computing the error probability for coding or modulation. In many cases, distance spectrum needs to be provided for analyze the Maximum likelihood decoding. However, it is difficult for computing the distance spectrum for a combined coding with modulation because of a nonlinear structure inside. In this thesis, we first build an augmented trellis for the combined coding with modulation. Applying the concept of difference by exclusive OR and regular subtraction to the augmented trellis, we build an improved virtual trellis. As a consequence the distance spectrum for our problem can be computed because of the linear structure of the virtual trellis. The distance spectrum for different convolutional codes and CPM systems are investigated by us. Experiments results have demonstrate that a better distance spectrum implies a better error ability.

Combined coding with modulation is an important topic. Conventionally, the free distance is taken as the principle criterion for computing the error probability for coding or modulation. In many cases, distance spectrum needs to be provided for analyze the Maximum likelihood decoding. However, it is difficult for computing the distance spectrum for a combined coding with modulation because of a nonlinear structure inside. In this thesis, we study the order of distance spectrum members to find some limited number of members to present the whole distance spectrum. In our previous work, we have built an augmented trellis for the combined coding with modulation. Applying the concept of difference by exclusive OR and regular subtraction to the augmented trellis, we build an improved virtual trellis. In this thesis, we expend the concept of subtraction to a pair relation. Thus, this augmented trellis is first composed of paired states and transition lines. Then, we use a partition principle to group the states and lines. Finally, the complex trellis is reduced to a reasonable structure. We therefore can apply distance spectrum computing algorithm to find the distance spectrum. The distance spectrum for different convolution codes and CPM systems are investigated by us. Experiments results have demonstrate this distance spectrum is more accurate than before.

No description available.

Fuzzy Cognitive Maps (FCMs) are a widely used, neuro-fuzzy based qualitative approach for the modeling of dynamic systems, which allow for both static and dynamic analyses. They are capable of modeling complex systems with nonlinearities and unknown physical behaviour. FCMs describe a given system by means of concepts connected by quantified cause-effect relationships. This dissertation contributes to the subject of computer-driven generation of FCMs that can be used to perform an accurate dynamic analysis of the modeled system. The dynamic analysis provides insights into the degree of presence, and dependencies between the concepts in successive iterations of the simulation of a given FCM model. Such simulation studies could be used to analyze what-if scenarios in the context of decision support and to perform time series predictions. Two research directions within the framework of FCM development, which concern the learning of FCMs from historical data and an aggregation of FCMs that were proposed by multiple experts, are investigated. Several new automated computational methods for data-driven learning and aggregation of FCMs are introduced and empirically evaluated. These methods utilize real-coded genetic algorithms (RCGA)-based optimization. This choice of the optimization vehicle was motivated by their well-documented efficiency in searching large and continuous search spaces, which are inherent to our problem. Experimental evaluation demonstrates that the proposed RCGA-based learning method outperforms modern existing approaches when the dynamic analysis is considered. A novel divide and conquer-based learning strategy to improve scalability of the RCGA approach, is also proposed. This strategy is shown to be competitive or even better than solutions based on the parallelization of the underlying genetic algorithm. The RCGA-based learning method is further extended to provide improved FCMs when the number of connections of the map is known a priori. Experimental evaluation shows that the density-based learning method outperforms the generic RCGA-based approach when using a relatively accurate density estimate, and that both methods are equivalent when the estimate is inaccurate. In addition, a novel method for the aggregation of multiple input FCMs, is proposed. When compared to existing aggregation approaches, this method provides solutions that are more accurate when dynamic analysis is the objective. / Software Engineering and Intelligent Systems

Thesis (M.S.)--Ohio University, November, 2003. / Title from PDF t.p. Includes bibliographical references (leaves 68-70).

This paper will examine color-coded musical notation. The history of color and music will be briefly explored before a more in-depth analysis of the widely available color-coded curriculums. Traditional method book formats will be examined for the potential integration of color-coded musical notation.

Doppler ultrasound imaging modalities arguably represent one of the most complex task performed (usually in real time) by ultrasound scanners. At the heart of these techniques lies the ability to detect and estimate soft tissues or blood motion within the human body. As they have become an invaluable tool in a wide range of clinical applications, these techniques have fostered an intensive effort of research in the field of signal processing for more than thirty years, with a push towards more accurate velocity or displacement estimation. Coded excitation has recently received a growing interest in the medical ultrasound community. The use of these techniques, originally developed in the radar field, makes it possible to increase the depth of penetration in B-mode imaging, while complying with safety standards. These standards impose strict limits on the peak acoustic intensity which can be transmitted into the body. Similar solutions were proposed in the early developments of Doppler flow-meters to improve the resolution / sensitivity trade-off from which typical pulsed Doppler systems suffer. This work discusses the potential improvements in resolution, sensitivity and accuracy achievable in the context of modern Doppler ultrasound imaging modalities (taken in its broadest sense, that is, all the techniques involving the estimation of displacements, or velocities). A theoretical framework is provided for discussing this potential improvements, along with simulations for a more quantitative assessment. Colour Flow Imaging (CFI) modalities are taken as the main reference technique for discussion, due to their historical importance, and their relevance in many clinical applications. The potential achievable improvement in accuracy is studied in the context of modern velocity estimation strategies, which can be broadly classified into narrowband estimators (such as the “Kasai” estimator still widely used in CFI) and time shift based wideband strategies (normalised crosscorrelation estimator used, for instance, in applications like strain or strain rate estimation, elastography, etc.). Finally, simulations and theoretical results are compared to experimental data obtained with a simple custom-designed experimental set-up, using a single-element transducer.

Non-linear continuous phase modulation has constant envelope and spectral efficiency, which are desirable for public safety communication systems where both bandwidth and power are limited. A practical design of an innovation based receiver for partial response CPM was recently developed for public safety applications. It is in the form of a linear predictive demodulator with a coefficient look up table. The demodulator shows great performance over multipath fading channels without channel equalization and promises a significant contribution to public safety communication. The work in this thesis is focussed on developing and analyzing modern techniques to improve the receiver performance while maintaining a feasible implementation complexity. Suitable soft output algorithms are incorporated into the demodulator allowing a subsequent convolutional decoder to perform soft decoding. By modifying the design criteria of the predictive demodulator and introducing a feedback loop, an iterative detection scheme is formed for the concatenated structure of demodulator, deinterleaver and decoder. Spatial diversity combining techniques are summarized and a very low complexity combining scheme is developed. It selects the best received sample sequence by considering the average energy of each sequence. In addition, the demodulator is extended to have dual coefficient look up tables supporting its detection by having parallel prediction processes and combining their results. This leads to an improvement in overall demodulator performance. A theoretical proof that only half the number of coefficients need to be stored in memory is also given. Matlab simulations on a Rayleigh fast fading multipath channel have shown that the proposed techniques significantly improve the overall detection accuracy. Each of them provides a good gain in signal to noise ratio or delay spread and when combined, a significant performance gain is achieved.

Trellis-coded modulation (TCM) is a known technique to increase the data rate without increasing the channel bandwidth when implementing error correction coding. TCM is a combination of M-ary modulation and error correction coding. This thesis investigates the performance of a low spectral efficiency TCM system, which is compared with three alternative systems having comparable bandwidth. The three alternative systems are all non-TCM systems and consist of QPSK with independent r=1/2 error correction coding on the in-phase and quadrature components, 8-ary biorthogonal keying (8-BOK) with r=2/3 error correction coding, and 16-BOK with r=3/4 error correction coding. The effects of both additive white Gaussian noise (AWGN) and pulse-noise interference (PNI) are considered. The TCM system shows much better than expected performance and significant resistance to PNI, and performance improves as the number of memory element increases. The alternative QPSK system with soft decision decoding (SDD) experiences significant degradation with PNI. The 8-BOK with r=2/3 error correction and 16-BOK with r=3/4 error correction systems occupy approximately the same bandwidth as the TCM system and show better performance in PNI than the alternative QPSK system.