A design decomposition-integration model, named COPE, is proposed in which Axiomatic Design Matrices (DM) map Functional Requirements to Design Parameters while Design Structure Matrices (DSM) provide structured representation of the system development context. In COPE, the DM and the DSM co-evolve. Traversing between the two types of matrices allows for some control in the application of the s...

This study proposes the RO-RA-RV structure for rule-based knowledge and integrates methods of conditional probability, vector matrices, and artificial intelligence to establish a conditional probability knowledge similarity algorithm and calculation system. This calculation system can quickly and accurately calculate rule-based knowledge similarity matrices and determine the relationship among ...

In this paper, a new nonparametric feature extraction method is proposed for high dimensional multiclass pattern recognition problems. It is based on a nonparametric extension of scatter matrices. There are at least two advantages to using the proposed nonparametric scatter matrices. First, they are generally of full rank. This provides the ability to specify the number of extracted features de...

In this paper we study decidability and complexity of decision problems on matrices from the special linear group SL(2,Z). In particular, we study the freeness problem: given a finite set of matrices G generating a multiplicative semigroup S, decide whether each element of S has at most one factorization over G. In other words, is G a code? We show that the problem of deciding whether a matrix ...

Despite their successes, what makes kernel methods difficult to use in many large scale problems is the fact that storing and computing the decision function is typically expensive, especially at prediction time. In this paper, we overcome this difficulty by proposing Fastfood, an approximation that accelerates such computation significantly. Key to Fastfood is the observation that Hadamard mat...

Simulating quantum computation on a classical computer is a difficult problem. The matrices representing quantum gates, and vectors modeling qubit states grow exponentially with an increase in the number of qubits. However, by using a novel data structure called the Quantum Information Decision Diagram (QuIDD) that exploits the structure of quantum operators, many of these matrices and vectors ...

Simulating quantum computation on a classical computer is a difficult problem. The matrices representing quantum gates, and vectors modeling qubit states grow exponentially with an increase in the number of qubits. However, by using a novel data structure called the Quantum Information Decision Diagram (QuIDD) that exploits the structure of quantum operators, many of these matrices and vectors ...

objective eudragits are widely used polymers in the production of oral sustained release dosage forms. the application of these polymers in the production of inert insoluble matrices has been investigated. however the effect of particle size, compaction force and presence of aerosil 200 as a glidant on the properties of eudragit rs and rl matrices prepared by direct compression of their physica...

We present a new single-chip texture classifier based on the cellular neural network (CNN) architecture. Exploiting the dynamics of a locally interconnected 2D cell array of CNNs we have developed a theoretically new method for texture classification and segmentation. This technique differs from other convolution-based feature extraction methods since we utilize feedback convolution, and we use...