Recently there are various requirements for LSI testing, such as test compaction, test compression, low power dissipation or increase of defect coverage. If test sequences contain lots of don't cares (Xs), then their flexibility can be used to meet the above requirements. In this paper, we propose methods for finding as many Xs as possible in test sequences for sequential circuits. Given a fully specified test sequence generated by a sequential ATPG, the proposed methods produce a test sequence containing Xs without losing stuck-at fault coverage of the original test sequence. The methods apply an approach based on fault simulation, and they introduce some heuristics for reducing the simulation effort. Experimental results for ISCAS'89 benchmark circuits show the effectiveness of the proposed methods.

Data mining across different companies, organizations, online shops, or the likes is necessary so as to discover valuable shared patterns, associations, trends, or dependencies in their shared data. Privacy, however, is a concern. In many situations it is required that data mining should be conducted without any privacy being violated. In response to this requirement, in this paper we propose an effective distributed privacy-preserving data mining approach called SDDM. SDDM is characterized by its ability to resist collusion. Unless the number of colluding sites in a distributed system is larger than or equal to 4, privacy cannot be violated. Results of performance study demonstrated the effectiveness of SDDM.

This paper presents a linear constrained minimum variance multiuser detection (MUD) scheme for DS-CDMA systems, which makes full use of the available spreading sequences of the users as well as the relevant channel information of the incoming rays in the construction of the constraint matrix. To further enhance the performance, a statistical optimum filter bank in combination with the developed minimum variance MUD with the partitioned linear interference canceller (PLIC) as the underlying structure is also addressed. The determination of the filter bank coefficients, however, calls for computationally demanding nonlinear programming. To alleviate the computational overhead, an iterative procedure is also proposed, which solves the Rayleigh quotient in each iteration. Furthermore, the expressions of the output signal to interference plus noise ratio (SINR) are also determined to provide further insights into the proposed approach. Conducted simulations validate the new scheme.

This paper deals with computation of parallel degree, PARAdeg, for (dataflow) program nets with SWITCH-nodes. Ge et al. have given the definition of PARAdeg and an algorithm of computing PARAdeg for program nets with no SWITCH-nodes. However, for program nets with SWITCH-nodes, any algorithm of computing PARAdeg has not been proposed. We first show that it is intractable to compute PARAdeg for program nets with SWITCH-nodes. To do this, we define a subclass of program nets with SWITCH-nodes, named structured program nets, and then show that the decision problem related to compute PARAdeg for acyclic structured program nets is NP-complete. Next, we give a heuristic algorithm to compute PARAdeg for acyclic structured program nets. Finally, we do experiments to evaluate our heuristic algorithm for 200 acyclic structured program nets. We can say that the heuristic algorithm is reasonable, because its accuracy is more than 96% and the computation time can be greatly reduced.

In computer simulation of a large number of moving objects (MOs), how to enlarge Δt (the interval between the simulation time steps) without introducing causality errors is one of the primary keys to enhancing performance. Causality errors can be avoided by using the same Δt among related MOs when they are in the scene of detection (SoD). But in a large-scale MO simulation, MOs interact with one another in a complicated manner requiring a large calculation cost to predict the beginning time of SoD. In this paper we propose an event-aware dynamic time step synchronization method (DTSS) for distributed MO simulation, which increases Δt without introducing causality errors and speeds up the simulation. DTSS can be implemented with little calculation cost because: (1) DTSS does not calculate the beginning time of SoD exactly, but calculates the time for possible entry into SoD with a simple mechanisim, and (2) MO simulation consists of a "movement"-phase and a "detection"-phase in which the distance-calculation between MOs requires a heavy load, and DTSS utilizes the distance values to calculate Δt. In this paper, we also discuss a suitable HLA based time management mechanism to implement DTSS on a distributed computing environment. In the performance evaluation of DTSS, the calculation cost of DTSS is implemented by using the HLA suitable time management mechanism. The results show that DTSS can be executed within the ideal time plus its 1% over-cost when a basic scenario of war-game simulation is employed. Therefore if the ratio of SoD to the total simulation is small, the execution time is expected to decrease to nearly this ratio. We also introduce the criterion for determining when DTSS is superior to the conventional method by using the performance evaluation results. The results presented in this paper are effectively utilized when DTSS is applied to practical applications.

An integrate-and-fire-type spiking feedback network is discussed in this paper. In our spiking neuron model, analog information expressing processing results is given by the relative relation of spike firing. Therefore, for spiking feedback networks, all neurons should fire (pseudo-)periodically. However, an integrate-and-fire-type neuron generates no spike unless its internal potential exceeds the threshold. To solve this problem, we propose negative thresholding operation. In this paper, this operation is achieved by a global excitatory unit. This unit operates immediately after receiving the first spike input. We have designed a CMOS spiking feedback network VLSI circuit with the global excitatory unit for Hopfield-type associative memory. The circuit simulation results show that the network achieves correct association operation.

Petri nets have recently become widely accepted as a description method for biological pathways by researchers in computer science as well as those in biology. This paper gives an overview of Petri net formalisms to describe biological pathways and discusses their use in modelings and simulations for the systematic understandings of biological pathways. After reviewing the use of various types of Petri nets for the biological pathway modelings, we showed the examples that analyze fundamental properties of biological pathways using T-invariant, P-invariant, siphon, and trap. Applications of hybrid Petri nets for producing new biological hypotheses through simulations are also illustrated.

This paper deals with the Optimum Communication Spanning Tree Problem (OCST) which is well known as an NP-hard problem. For solving the problem, we uses an evolutionary approach. This paper presents a new effective tree encoding and proposes a tree construction routine (TCR) to generate a tree from the encoding. The basic principle is to break a cycle. We also propose a new crossover operator that focuses on the inheritance of parental information and the use of network information. Consequently, we confirm that the proposed algorithm is superior to other algorithms applied to the OCST problem or other tree problems. Moreover, our method can find a better solution than the solution which was previously known as the best solution. In addition, we analyzed the locality and diversity property of encoding and observed that the proposed method has high locality and at the same time it preserves population diversity for many generations. Finally, we conclude that these properties are the main reasons why the proposed method outperforms the other encodings.

This work presents an application of the previously proposed Support Vector Machines Based Generalized Predictive Control (SVM-Based GPC) method [1] to the problem of controlling chaotic dynamics with small parameter perturbations. The Generalized Predictive Control (GPC) method, which is included in the class of Model Predictive Control, necessitates an accurate model of the plant that plays very crucial role in the control loop. On the other hand, chaotic systems exhibit very complex behavior peculiar to them and thus it is considerably difficult task to get their accurate model in the whole phase space. In this work, the Support Vector Machines (SVMs) regression algorithm is used to obtain an acceptable model of a chaotic system to be controlled. SVM-Based GPC exploits some advantages of the SVM approach and utilizes the obtained model in the GPC structure. Simulation results on several chaotic systems indicate that the SVM-Based GPC scheme provides an excellent performance with respect to local stabilization of the target (an originally unstable equilibrium point). Furthermore, it somewhat performs targeting, the task of steering the chaotic system towards the target by applying relatively small parameter perturbations. It considerably reduces the waiting time until the system, starting from random initial conditions, enters the local control region, a small neighborhood of the chosen target. Moreover, SVM-Based GPC maintains its performance in the case that the measured output is corrupted by an additive Gaussian noise.

An optically scanning electromagnetic field probe system consisting of an electro-optic or magneto-optic crystal and a galvano scanner is proposed for high-speed electromagnetic field distribution measurements. We used this technique to measure electromagnetic field distributions near printed circuit boards or ICs to address electromagnetic compatibility problems or in designing electronic devices. With our scanning system, we can measure the electric field intensities of about 40,000 points with an area of 4040 mm in about 3 minutes (4 ms per point) up to 2.7 GHz. We measured the electric near-field distribution above a five-split transmission line using a cadmium telluride (CdTe) electro-optic crystal. The measurement results showed that the spatial resolution of the system was less than 400 µm in the case of a common current with a crystal thickness of 1 mm. The electric near-field distribution above a microstrip line filter was measured using LiNbO3 electro-optic crystal. Changes in the distribution according to the frequency were observed. The experimental results obtained using this system were compared with simulation results obtained using a finite-difference time-domain method. The overall results indicated that the measurement system is capable of accurately measuring electric near-fields. We also discuss the invasiveness of the measurement system, due to the electro-optic crystals, in terms of both the experimental and simulated results.

An alternative human interface enabling the handicapped with severe motor disabilities to control an assistive system is presented. Since this interface relies on the biosignals originating from the contraction of muscles on the face during particular movements, even individuals with a paralyzed limb can use it with ease. For real-world application, a dedicated hardware module employing a general-purpose DSP was implemented and its validity tested on an electrically powered wheelchair. Furthermore, an additional attempt to reduce error rates to a minimum for stable operation was also made based on the entropy information inherent in the signals during the classification phase. In the experiments in which 11 subjects participated, it was found most of them could control the target system at their own will, and thus the proposed interface could be considered a potential alternative for the interaction of the severely handicapped with electronic systems.

In this paper, we propose a new multiuser detection scheme using Maximum Likelihood (ML) criterion and the M algorithm for Multi Carrier (MC)-Code Division Multiple Access (CDMA) systems in the down-link channel. We first describe an implementation of ML detection separating In- and Quadrature-phase components and using well-known linear filters. In the proposed algorithm, we produce hypothesis symbol vectors in a tree structure by partly changing the sub-optimum hard decisions based on the linear filter output. At each stage, we adopt the best M likely paths with respect to the true log likelihood or distance function as survivors. We determine the symbol vector which minimizes the distance function at the final stage. Although the complexity of ML detector is exponentially increasing as a function of the number of users, the proposed scheme requires by far less complexity. We demonstrate that the proposed scheme achieves equivalent Bit Error Rate (BER) performance with lower complexity in comparison with ML detector by computer simulations. Moreover we compare the proposed detection scheme with QRD-M algorithm which is based on QR decomposition combined with M algorithm.

In this paper, we propose a variational method to derive the coefficients of piecewise-linear (PWL) models able to accurately approximate nonlinear functions, which are vector fields of autonomous dynamical systems described by continuous-time state-space models dependent on parameters. Such dynamical systems admit limit cycles, and the supercritical Hopf bifurcation normal form is chosen as an example of a system to be approximated. The robustness of the approximations is checked, with a view to circuit implementations.

A network based on the Inverse Function Delayed (ID) model which can recall a temporal sequence of patterns, is proposed. The classical problem that the network is forced to make long distance jumps due to strong attractors that have to be isolated from each other, is solved by the introduction of the ID neuron. The ID neuron has negative resistance in its dynamics which makes a gradual change from one attractor to another possible. It is then shown that a network structure consisting of paired conventional and ID neurons, perfectly can recall a sequence.

In this paper, we propose two techniques to solve the nonlinear constrained optimization problem in large scale mesh-interconnected system. The first one is a diagram-method-based decomposition technique which decomposes the large scale system into some small subsystems. The second technique is a projected-Jacobi-based parallel dual-type method which can solve the optimization problems in the decomposed subsystems efficiently. We have used the proposed algorithm to solve numerous examples of large scale constrained optimization problems in power system. The test results show that the proposed algorithm has computational efficiency with respect to the conventional approach of the centralized Newton method and the state-of-the-art Block-Parallel Newton method.

If the signal is not Gaussian, then the power spectral density (PSD) approach is insufficient to analyze signals and we resort to estimate the higher order spectra of the signal. However, estimation of the higher order spectra is even more time consuming, for example, the complexity of trispectrum is O(N 4). This problem becomes even more serious when short time Fourier transform (STFT) is computed - computation of the trispectrum is required after every shift of the window. In this paper, a method to recursively compute trispectrum has been presented and it is shown that the computational complexity, for a window size of N, is reduced to be O(N 3) and is the same as the space complexity.

Modern processors have large instruction windows to improve performance. They usually adopt register renaming, where every active instruction with a valid destination needs a physical register. As the instruction windows get larger, however, bigger physical register files are required. To solve this problem, we proposed a physical register sharing technique. It shares a physical register among multiple instructions based on a value similarity. As a result, we achieved performance improvement without increasing the size of the physical register file. In addition, the proposed technique can also be used to reduce the timing, complexity and area overhead of the physical register file.

The decorrelating detector is one of the detecting methods in a direct sequence code division multiple access systems. We investigate the blind adaptive decorrelating detector (BADD) using only the signature of the desired user (DU) according to the assumption that the algorithm is used in downlink. When the BADD is constructed with an antenna array, both the spatial and temporal signature must be taken into consideration for signal detection. We propose the BADD incorporated with the blind estimation of spatial signature (SS) of the DU only from the received signals. As the estimation procedure of SS, the orthogonal projection approximation and subspace tracking algorithm is adopted. The proposed BADD presented the BER improvement with using antenna array. The BER performance has a lower limit with increasing the number of antenna array elements.

We introduce an extension of Golay complementary sequences in which, for each sequence, there exists another sequence such that the sum of aperiodic autocorrelation functions of these two sequences for a given multiple L-shift (L≥1) is zero except for the zero shift. We call these sequences multiple L-shift complementary sequences. It is well-known that the peak-to-average power ratio (PAPR) value of any Golay complementary sequence is less than or equal to 2. In this paper, we show that the PAPR of each multiple L-shift complementary sequence is less than or equal to 2L. We also discuss other properties of the sequences and consider their construction.

The global Lanczos algorithm for solving the RLCG interconnect circuits is presented in this paper. This algorithm is an extension of the standard Lanczos algorithm for multiple-inputs multiple-outputs (MIMO) systems. A new matrix Krylov subspace will be developed first. By employing the congruence transformation with the matrix Krylov subspace, the two-side oblique projection-based method can be used to construct a reduced-order system. It will be shown that the system moments are still matched. The error of the 2q-th order system moment will be derived analytically. Furthermore, two novel model-order reduction techniques called the multiple point global Lanczos (MPGL) method and the adaptive-order global Lanczos (AOGL) method which are both based on the multiple point moment matching are proposed. The frequency responses using the multiple point moment matching method have higher coherence to the original system than those using the single point expansion method. Finally, simulation results on frequency domain will illustrate the feasibility and the efficiency of the proposed methods.