ИНТЕЛЛЕКТУАЛЬНЫЙ числовым программным ДЛЯ MIMD-компьютер

For most scientific and engineering problems simulated on computers the solving of problems of the computational mathematics with approximately given initial data constitutes an intermediate or a final stage. Basic problems of the computational mathematics include the investigating and solving of linear algebraic systems, evaluating of eigenvalues and eigenvectors of matrices, the solving of systems of non-linear equations, numerical integration of initial- value problems for systems of ordinary differential equations.Для більшості наукових та інженерних задач моделювання на ЕОМ рішення задач обчислювальної математики з наближено заданими вихідними даними складає проміжний або остаточний етап. Основні проблеми обчислювальної математики відносяться дослідження і рішення лінійних алгебраїчних систем оцінки власних значень і власних векторів матриць, рішення систем нелінійних рівнянь, чисельного інтегрування початково задач для систем звичайних диференціальних рівнянь.Для большинства научных и инженерных задач моделирования на ЭВМ решение задач вычислительной математики с приближенно заданным исходным данным составляет промежуточный или окончательный этап. Основные проблемы вычислительной математики относятся исследования и решения линейных алгебраических систем оценки собственных значений и собственных векторов матриц, решение систем нелинейных уравнений, численного интегрирования начально задач для систем обыкновенных дифференциальных уравнений

ON SOME COMMON COMPRESSIVE SENSING RECOVERY ALGORITHMS AND APPLICATIONS

Compressive Sensing, as an emerging technique in signal processing is reviewed in this paper together with its’ common applications. As an alternative to the traditional signal sampling, Compressive Sensing allows a new acquisition strategy with significantly reduced number of samples needed for accurate signal reconstruction. The basic ideas and motivation behind this approach are provided in the theoretical part of the paper. The commonly used algorithms for missing data reconstruction are presented. The Compressive Sensing applications have gained significant attention leading to an intensive growth of signal processing possibilities. Hence, some of the existing practical applications assuming different types of signals in real-world scenarios are described and analyzed as well

Robust and Secure Watermarking Using Sparse Information of Watermark for Biometric Data Protection

Biometric based human authentication system is used for security purpose in many organizations in the present world. This biometric authentication system has several vulnerable points. Two of vulnerable points are protection of biometric templates at system database and protection of biometric templates at communication channel between two modules of biometric authentication systems. In this paper proposed a robust watermarking scheme using the sparse information of watermark biometric to secure vulnerable point like protection of biometric templates at the communication channel of biometric authentication systems. A compressive sensing theory procedure is used for generation of sparse information on watermark biometric data using detail wavelet coefficients. Then sparse information of watermark biometric data is embedded into DCT coefficients of host biometric data. This proposed scheme is robust to common signal processing and geometric attacks like JPEG compression, adding noise, filtering, and cropping, histogram equalization. This proposed scheme has more advantages and high quality measures compared to existing schemes in the literature

Cognitive computation of compressed sensing for watermark signal measurement

As an important tool for protecting multimedia contents, scrambling and randomizing of original messages is used in generating digital watermark for satisfying security requirements. Based on the neural perception of high-dimensional data, compressed sensing (CS) is proposed as a new technique in watermarking for improved security and reduced computational complexity. In our proposed methodology, watermark signal is extracted from the CS of the Hadamard measurement matrix. Through construction of the scrambled block Hadamard matrix utilizing a cryptographic key, encrypting the watermark signal in CS domain is achieved without any additional computation required. The extensive experiments have shown that the neural inspired CS mechanism can generate watermark signal of higher security, yet it still maintains a better trade-off between transparency and robustness

Wireless sensor system for infrastructure health monitoring

In this thesis, radio frequency identification (RFID)-based wireless sensor system for infrastructure health monitoring (IHM) is designed and developed. It includes mountable semi-passive tag antenna integrated sensors capable of measuring critical responses of infrastructure such as dynamic acceleration and strain. Furthermore, the system is capable of measuring structural displacement. One of the most important parts of this system is the relatively small, tunable, construction material mountable RFID tag antenna. The tag antenna is electronically integrated with the sensors. Leading to the process of developing tag antenna integrated sensors having satisfactory wireless performance (sensitivity and read range) when mounted on concrete and metal structural members, the electromagnetic performance of the tag antenna is analyzed and optimized using both numerical and experimental procedures. Subsequently, it is shown that both the simulation and the experimental measurement results are in good agreement. The semi-passive RFID-based system is implemented in a wireless IHM system with multiple sensor points to measure dynamic acceleration and strain. The developed system can determine the natural frequencies of infrastructure and identify any state changes of infrastructure by measuring natural frequency shifts. Enhancement of the spectral bandwidth of the system has been performed under the constraints of the RFID hardware. The influence of the orientation and shape of the structural members on wireless power flow in the vicinity of those members is also investigated with the RFID reader-tag antenna system in both simulation and experiments. The antenna system simulations with a full-scale structural member have shown that both the orientation and the shape of the structural member influence the wireless power flow towards and in the vicinity of the member, respectively. The measurement results of the conducted laboratory experiments using the RFID antenna system in passive mode have shown good agreement with simulation results. Furthermore, the system’s ability to measure structural displacement is also investigated by conducting phase angle of arrival measurements. It is shown that the system in its passive mode is capable of measuring small structural displacements within a short wireless distance. The benchmarking of the developed system with independent, commercial, wired and wireless measurement systems has confirmed the ability of the RFID-based system to measure dynamic acceleration and strain. Furthermore, it has confirmed the system’s ability to determine the natural frequency of an infrastructure accurately. Therefore, the developed system with wireless sensors that do not consume battery power in data transmission and with the capability of dynamic response measurement is highly applicable in IHM