A stock selection strategy using fuzzy neural networks

This paper describes, from a general system-design perspective, an artificial neural network (ANN) approach to a stock selection strategy. The paper suggests a concept of neural gates which are similar to the processing elements in ANN, but generalized into handling various types of information such as fuzzy logic, probabilistic and Boolean information together. Forecasting of stock market returns, assessing of country risk and rating of stocks based on fuzzy rules, probabilistic and Boolean data can be done using the proposed neural gates. Fuzzy logic is known to be useful for decision-making where there is a great deal of uncertainty as well as vague phenomena, but lacks the learning capability; on the other hand, neural networks are useful in constructing an adaptive system which can learn from historical data, but are not able to process ambiguous rules and probabilistic data sets. This paper describes how these problems can be solved using the proposed neural gates.     

Developing the Methods of Reliability Estimation for Structurally Complex Systems of Multistate Elements

For systems of multistate elements, the problem of developing Boolean reliability models was considered on the basis of multivalued logic, cortege algebra, algebra of groups of incompatible events, and classical logic-and-probabilistic method. Development of Boolean reliability models based on the multivalued logic was shown to be unadvisable. Numerical examples demonstrating applicability of the logic-and-probabilistic methods and their new capabilities were presented. Prospects of formulating a set of different problems that are tackled by the same logic-and-probabilistic methods with the aim of developing methods for calculation of the operational effectiveness of various levels of operability were emphasized. The possibility of constructing models for continual calculations on the basis of logic-and-probabilistic methods was demonstrated.     

The effect of presynaptic inhibition in switching neurostructures

A presynaptic inhibition function is described based on the language of Boolean algebra. A Fibonacci neuron is adduced as the equivalent of the sequential composition of such functions. Effective implementations of logic circuits are proposed. Affine transformations of necessary arguments are determined by Walsh spectral representations. The complexity of switching neural networks with dual neurons is analyzed.     

Time-based operators for relational algebra query languages

We present a new approach for historical relational algebra languages based upon generalized logic for Boolean and comparison operators and a temporal modification of the standard relational algebra operators. Historical versions of standard (snapshot) relational algebra operators based upon this generalized logic are presented. The temporal modification employs a logic that operates on sets of value/time-interval pairs and which can be applied to snapshot as well as historical databases. Our emphasis is that the generalized operators can be used to enrich existing historical query languages and to provide an easier and more natural time-based interface. Using the generalized operators, users can express their queries more naturally, succinctly and elegantly. Examples are presented which illustrate that the modified operators offer a good degree of flexibility in expressing different temporal requirements.     

逻辑函数的双逻辑综合与优化

针对传统布尔逻辑在电路面积优化中存在的不足,提出了一种用传统布尔逻辑和Reed-Muller(RM)逻辑相结合的双逻辑优化算法.通过将原逻辑函数的乘积项转化为不相交乘积项,并利用不相交乘积项的位操作,将逻辑函数的覆盖分成2个部分,使之分别适合布尔逻辑综合和RM逻辑综合;同时提出了适合双逻辑函数的逻辑功能验证方法.双逻辑优化算法用C语言编程实现并用MCNC标准电路进行测试.实验结果表明,与单一的布尔逻辑综合结果相比,在绝大多数情况下文中算法可使电路面积获得进一步优化.     

Maximal contractions in Boolean algebras

In the present paper,the concepts of deductive element and maximal contraction are introduced in Boolean algebras,and corresponding theories of consistency and maximal contractions are studied.An algorithm principle is proposed to compute all maximal contractions for a consistent set with respect to its refutation in Boolean algebras.It is pointed out that the quotient algebra of the first-order language with respect to its provable equivalence relation constitutes a Boolean algebra,and hence the computation of R-contractions for closed formulas in first-order languages can be converted into the one in Boolean algebras proposed in this paper.Furthermore,the concept of basic element is introduced in Boolean algebras,which contributes to the definitions of clause and Horn clause transplanted from logic to a special type of Boolean algebras generated by basic elements.It is also pointed out that the computation of R-contractions for clauses in the classical propositional logic can be converted into the one in Boolean algebras generated by basic elements proposed in this paper.     

Extension of belief functions to infinite-valued events

We generalise belief functions to many-valued events which are represented by elements of Lindenbaum algebra of infinite-valued ?ukasiewicz propositional logic. Our approach is based on mass assignments used in the Dempster–Shafer theory of evidence. A generalised belief function is totally monotone and it has Choquet integral representation with respect to a unique belief measure on Boolean events.     

Refinement algebra with dual operator

Algebras of imperative programming languages have been successful in reasoning about programs. In general an algebra of programs is an algebraic structure with programs as elements and with program compositions (sequential composition, choice, skip) as algebra operations. Various versions of these algebras were introduced to model partial correctness, total correctness, refinement, demonic choice, and other aspects. We introduce here an algebra which can be used to model total correctness, refinement, demonic and angelic choice. The basic model of our algebra are monotonic Boolean transformers (monotonic functions from a Boolean algebra to itself).     

To the problem of realizability of Boolean functions by circuits in a basis of unreliable functional elements

Maximal extensions of Post classes containing 0, 1, and x in the algebra of partially unreliable Boolean functions are described. Based on these extensions, criteria of expressibility of Boolean functions by circuits in a basis of partially unreliable elements are proved.     

Applicability of feed-forward and recurrent neural networks to Boolean function complexity modeling

In this paper, we present the feed-forward neural network (FFNN) and recurrent neural network (RNN) models for predicting Boolean function complexity (BFC). In order to acquire the training data for the neural networks (NNs), we conducted experiments for a large number of randomly generated single output Boolean functions (BFs) and derived the simulated graphs for number of min-terms against the BFC for different number of variables. For NN model (NNM) development, we looked at three data transformation techniques for pre-processing the NN-training and validation data. The trained NNMs are used for complexity estimation for the Boolean logic expressions with a given number of variables and sum of products (SOP) terms. Both FFNNs and RNNs were evaluated against the ISCAS benchmark results. Our FFNNs and RNNs were able to predict the BFC with correlations of 0.811 and 0.629 with the benchmark results, respectively.     

Algorithms for Synthesis of Polynomials Implementing Weakly Specified Boolean Functions and Systems

Weakly specified Boolean functions and systems are considered. A series of practically effective algorithms are proposed for their implementation by AND/EXOR circuits, which rely on the optimization of polynomial representations and the solutions of appropriate matrix logic equations. The obtained results are extended to multivalued logic.     

基于条件事件代数的贝叶斯网的逻辑推理

条件事件代数理论在数据融合系统中有着重要的应用前景,该理论可用来解决不确定性、概率性和模糊性推理问题。条件事件代数是在确保规则与条件概率相容的前提下,把布尔代数上的逻辑运算推广到条件事件(规则)集合中的逻辑代数系统。对于一些特殊的贝叶斯网(如多树型网络)已经有了一些可行的概率推理的算法,但到目前为止,还没有可行的逻辑推理的算法。随着对不确定性知识研究的深入,迫切需要具有逻辑推理的算法。论文介绍了乘积空间条件事件代数的定义和基本性质,提出了基于乘积空间条件事件代数的贝叶斯网的逻辑推理的算法以及应用。     

N-tuple algebra-based probabilistic logic

The concept of “probabilistic logic” known in artificial intelligence needs a more through substantiation. A new approach to constructing probabilistic logic based on the n-tuple algebra developed by the author is proposed. A brief introduction is given to the n-tuple algebra and its properties that provide efficient paralleling of algorithms for solving problems of logical analysis of systems in computer implementation are generalized. Methods for solving direct and inverse problems of probabilistic simulation of logical systems are considered.     

On the algebraic structure of binary lattice-valued fuzzy relations

From a general algebraic point of view, this paper aims at providing an algebraic analysis for binary lattice-valued relations based on lattice implication algebras—a kind of lattice-valued propositional logical algebra. By abstracting away from the concrete lattice-valued relations and the operations on them, such as composition and converse, the notion of lattice-valued relation algebra is introduced, LRA for short. The reduct of an LRA is a lattice implication algebra. Such an algebra generalizes Boolean relation algebras by general distributive lattices and can provide a fundamental algebraic theory for establishing lattice-valued first-order logic. Some important results are generalized from the classical case. The notion of cylindric filter is introduced and the generated cylindric filters are characterized.     

Boolean functions of an odd number of variables with maximum algebraic immunity

In this paper, we study Boolean functions of an odd number of variables with maximum algebraic immunity. We identify three classes of such functions, and give some necessary conditions of such functions, which help to examine whether a Boolean function of an odd number of variables has the maximum algebraic immunity. Further, some necessary conditions for such functions to have also higher nonlinearity are proposed, and a class of these functions are also obtained. Finally, we present a sufficient and necessary condition for Boolean functions of an odd number of variables to achieve maximum algebraic immunity and to be also 1-resilient.     

条件事件代数研究综述

综述了条件事件代数理论的原理、主要性质和应用．条件事件代数是一门新兴的解决不确定性、概率性和模糊性推理问题的学科,是在确保规则概率与条件概率相容的前提下,把布尔代数上的逻辑运算推广到条件事件(规则)集合中得到的代数系统,目的是为智能系统中的条件推理建立一个数学基础．该文也对比条件事件代数更一般的逻辑系统——关联事件代数理论进行了介绍．     

集合代数是经典命题演算形式系统的语义解释

经典命题演算形式系统(CPC)中的公式只是一些形式符号,其意义是由具体的解释给出的.逻辑代数和集合代数都是布尔代数,都是CPC的解释.集合代数是CPC的集合语义,其中对联结词的解释就是集合运算;对形式公式的解释就是集合函数;对逻辑蕴涵.逻辑等价的解释就是集合包含和集合相等=.标准概率逻辑是在标准概率空间上建立的逻辑体系,命题表示随机事件,随机事件是集合,概率空间中的事件域是集合代数,概率逻辑就是CPC集合语义的实际应用.CPC完全适用于概率命题演算.     

Pseudocomplemented lattice effect algebras and existence of states

We prove that in every pseudocomplemented atomic lattice effect algebra the subset of all pseudocomplements is a Boolean algebra including the set of sharp elements as a subalgebra. As an application, we show families of effect algebras for which the existence of a pseudocomplementation implies the existence of states. These states can be obtained by smearing of states existing on the Boolean algebra of sharp elements.     

Bounded algebra and current-mode digital circuits

This paper proposes two bounded arithmetic operations,which are easily realized with current signals.Based on these two operations,a bounded algebra system suitable for describing current-mode digital circuits is developed and its relationship with the Boolean algebra,which is suitable for representing voltagemode digital circuits,is investigated.Design procedure for current-mode circuits using the proposed algebra system is demonstrated on a number of common circuit elements which are used to realize arithmetic operations,such as adders and multipliers.     

Ratios of optimal values of objective functions of the knapsack problem and its linear relaxation

The ratios of the values of objective functions for optimal solutions of linear and integer knapsack problems are considered. Estimates for these ratios are obtained. One-dimensional and multi-dimensional knapsack problems with Boolean variables are studied experimentally. For these problems, a hypothesis is formulated on the asymptotic behavior of the ratio as the number of variables grows.