Analysis and Prediction of Electric Power System’s Stability Based on Virtual State Estimators

The stability of bilinear systems is investigated using spectral techniques such as selective modal analysis. Predictive models of bilinear systems based on inductive knowledge extracted by big data mining techniques are applied with associative search of statistical patterns. A method and an algorithm for the elementwise solution of the generalized matrix Lyapunov equation are developed for discrete bilinear systems. The method is based on calculating the sequence of values of a fixed element of the solution matrix, which depends on the product of the eigenvalues of the dynamics matrix of the linear part and the elements of the nonlinearity matrixes. A sufficient condition for the convergence of all sequences is obtained, which is also a BIBO (bounded input bounded output) systems stability condition for the bilinear system.

Buffer Compliance Control of Space Robots Capturing a Non-Cooperative Spacecraft Based on Reinforcement Learning

Aiming at addressing the problem that the joints are easily destroyed by the impact torque during the process of space robot on-orbit capturing a non-cooperative spacecraft, a reinforcement learning control algorithm combined with a compliant mechanism is proposed to achieve buffer compliance control. The compliant mechanism can not only absorb the impact energy through the deformation of its internal spring, but also limit the impact torque to a safe range by combining with the compliance control strategy. First of all, the dynamic models of the space robot and the target spacecraft before capture are obtained by using the Lagrange approach and Newton-Euler method. After that, based on the law of conservation of momentum, the constraints of kinematics and velocity, the integrated dynamic model of the post-capture hybrid system is derived. Considering the unstable hybrid system, a buffer compliance control based on reinforcement learning is proposed for the stable control. The associative search network is employed to approximate unknown nonlinear functions, an adaptive critic network is utilized to construct reinforcement signal to tune the associative search network. The numerical simulation shows that the proposed control scheme can reduce the impact torque acting on joints by 76.6% at the maximum and 58.7% at the minimum in the capturing operation phase. And in the stable control phase, the impact torque acting on the joints were limited within the safety threshold, which can avoid overload and damage of the joint actuators.

Accelerated preprocessing in task of searching substrings in a string

Introduction. A rapid development of the systems such as Yandex, Google, etc., has predetermined the relevance of the task of searching substrings in a string, and approaches to its solution are actively investigated. This task is used to create database management systems that support associative search. Besides, it is applicable in solving information security issues and creating antivirus programs. Algorithms of searching substring in a string are used in signature-based discovery tasks.Materials and Methods. The solution to the problem is based on the Aho-Corasick algorithm which is a typical technique of searching substrings in a string. At the same time, a new approach regarding preprocessing is employed.Research Results. The possibility of constructing the transition function and suffix references through suffix arrays and special mappings, is shown. The relationship between the prefix tree and suffix arrays was investigated, which provided the development of a fundamentally new method of constructing the transition and error functions. The results obtained enable to substantially shorten the time intervals spent on the preelection processing of a set of pattern strings when using an integer alphabet. The paper lists eight algorithms. The developed algorithms are evaluated. The results obtained are compared to the formerly known. Two theorems and eight lemmas are proved. Two examples illustrating features of the practical application of the developed preprocessing procedure are given.Discussion and Conclusions. The preprocessing procedure proposed in this paper is based on the communication between the suffix array built on the ground of a set of pattern strings and the construction of transition and error functions at the initial stages of the Aho-Corasick algorithm. This approach differs from the traditional one and requires the use of algorithms providing a suffix array in linear time. Thus, the algorithms that enable to significantly reduce the time for preprocessing of a set of pattern strings under the condition of using a certain type of alphabet in comparison to the known approach proposed in the Aho- Corasick algorithm are described. The research results presented in the paper can be used in antivirus programs that apply searching for signatures of malicious data objects in the memory of a computer system. In addition, this approach to solving the problem on searching substrings in a string will significantly speed up the operation of database management systems using associative search.

EFFECT OF INFLATION AND PRICE INDEX ON EQUITY ASSETS

The purpose of this study is to determine the effect of inflation and the equity price index on the net asset value of the Islamic Fixed Income Mutual Funds registered with the Financial Services Authority for the period from from 2011 to 2016. The type of search used is associative search. The data in this study are secondary historical data using Net Asset Value (NAV) and the share price index published by the Financial Services Authority (OJK), as well as inflation data published by Bank Indonesia for the period 2011-2016. The method used in this study uses regression analysis with panel data. The results show that inflation has a negative and significant impact on the net asset value. The equity price index has a positive and significant influence on the net asset value. Inflation and the equity price index simultaneously have a significant effect on the net asset value of Sharia mutual funds.

Fundamental Law of Memory Recall

Free recall of random lists of words is a standard paradigm used to probe human memory. We proposed an associative search process that can be reduced to a deterministic walk on random graphs defined by the structure of memory representations. The corresponding graph model is different from the ones considered in the past but still can be solved analytically, resulting in a novel parameter-free prediction for the average number of memory items recalled (RC) out of M items in memory: . This prediction was verified with a specially designed experimental protocol combining large-scale crowd-sourced free recall and recognition experiments with randomly assembled lists of words or common facts. Our theoretical and experimental results indicate that memory recall operates according to a stereotyped search process common to all people.

After Digital

We are surrounded by digital computers. They do many things well that humans do not and have transformed our lives. But all computers are not the same. Although digital computers dominate today’s world, alternative ways to “compute” might be better and more efficient than digital computation when mechanically performing those tasks, important to humans, that we think of as “cognition.” Cognition, after all, was originally developed to work with our own specific biological hardware. Digital computers require elaborate detailed instructions to work; they are flexible but not simple. Analog computers are designed to do specific tasks. They can be simple but not flexible. Hardware matters. The book discusses two classic kinds of computer, digital and analog, and gives examples of their history, functions, and limitations. The author suggest that when brain “hardware,” with its associated brain “software” work together, it could form a computer architecture that would be useful for the efficient performance of cognitive tasks. This book discusses the essentials of brain hardware—in particular, the cerebral cortex, where cognition lives—and how cortical structure can influence the form taken by the computational operations underlying cognition. Topics include association, understanding complex systems through analogy, formation of abstractions, and the biology of number and its use in arithmetic and mathematics. The author introduces novel “brain-like” control mechanisms: active associative search and traveling waves. There is discussion on computing across scales of organization from single neurons to brain regions containing millions of neurons.