The multi-step prediction model based on partial least squares (PLS) is established to predict short-term load series with high embedding dimension in this paper, which refrains from cumulative error with local single-step linear model, and can cope with the multi-collinearity in the reconstructed phase space. In the model, PLS is used to model the dynamic evolution between the phase points and the corresponding future points. With research on the PLS theory, the model algorithm is put forward. Finally, the actual load series are used to test this model, and the results show that the model plays well in chaotic time series prediction, even if the embedding dimension is selected a big value.

Consideration of manipulator dynamics and external disturbances in robot control system design can enhance the stability and performance properties of the whole system. In this paper, we present an approach to solve the control problem when the inertia parameters of robot are unknown, and at the same time robot is subjected to external force disturbances. This approach is based on simultaneous estimation of force signal and inertia parameters and utilizing them in the control law. The update laws and the control law are derived based on a single time-varying Lyapunov function, so that the global convergence of the tracking error is ensured. A theorem with a detailed proof is presented to guarantee the global uniform asymptotic stability of the whole system. Some simulations are made for a number of external forces to illustrate the effectiveness of the proposed approach.

A 3 dimensional (3D) error diffusion method based on edge detection for flat panel display (FPD) is presented. The new method diffuses errors to the neighbor pixels in current frame and the neighbor pixel in the next frame. And the weights of error filters are dynamically adjusted based on the results of edge detection in each pixel's processing, which makes the weights coincide with the local edge feathers of input image. The proposed method can reduce worm artifacts and improve reproduction precision of image details.

Network topology has no direct effect on the correctness of network protocols, however, it influences the performance of networks and their survivability when they are under attack. Recent studies have analyzed the robustness of the Internet in the face of faults or attacks which may cause node failures. However, the effect of link failure or a series of link failures has not been extensively examined, even though such a situation is more likely to occur in the current Internet environment. In this paper, we propose an attack-and-failure graph model and practical techniques for attacking strategies against nodes, edges or paths in order to reflect real-life attack scenarios. The resiliency of Internet topologies is examined under the attacking strategies, with various metrics including path-failure ratio and "attack power," which is defined as the ratio of the failure to attack. The experiments reveal that "path-based" attacks can result in greater damage to the connectivity of a network than the other types of attack. Nonetheless, the effectiveness of an attack depends on the objective that the attacker wants to achieve through the attack. The proposed simple but formalized approach can be a springboard for developing more resilient Internet topologies in a variety of aspects.

In this paper, we give an algorithm for the node-to-set disjoint paths problem in a transposition graph. The algorithm is of polynomial order of n for an n-transposition graph. It is based on recursion and divided into two cases according to the distribution of destination nodes. The maximum length of each path and the time complexity of the algorithm are estimated theoretically to be O(n7) and 3n - 5, respectively, and the average performance is evaluated based on computer experiments.

It is well known that speech captured in a room by distant microphones suffers from distortions caused by reverberation. These distortions may seriously damage both speech characteristics and intelligibility, and consequently be harmful to many speech applications. To solve this problem, we proposed a dereverberation algorithm based on multi-channel linear prediction. The method is as follows. First we calculate prediction filters that cancel out the room reverberation but also degrade speech characteristics by causing excessive whitening of the speech. Then, we evaluate the prediction-filter degradation to compensate for the excessive whitening. As the reverberation lengthens, the compensation performance becomes worse due to computational accuracy problems. In this paper, we propose a new computation that may improve compensation accuracy when dealing with long reverberation.

Effects of wall material on the channel capacity of an indoor multiple input multiple output (MIMO) system are investigated using a hybrid technique of the method of moments (MoM) and the finite difference time domain (FDTD) method with consideration of the Ricean K factor and the effective degrees of freedom (EDOF) of multiple paths.

Tone Injection (TI) can reduce the high peak-to-average ratio (PAR) which can substantially limit the performance of multicarrier systems without bandwidth loss. However, TI results in peak regrowth since it does not consider second peaks which can be higher than the peak after performing TI and also the average transmit power is increased because of huge constellation. In this paper, a no-rate loss PAR reduction technique, Injected Tone Constellation (ITC), is proposed along with an iterative algorithm to achieve the performance increase and to minimize the average transmit power without high complexity.

Let A(n, d, w) denote the maximum possible number of code words in binary (n,d,w) constant weight codes. For smaller instances of (n, d, w)s, many improvements have occurred over the decades. However, unknown instances still remain for larger (n, d, w)s (for example, those of n > 30 and d > 10). In this paper, we propose a new class of binary constant weight codes that fill in the remaining blank instances of (n, d, w)s. Specifically, we establish several new non-trivial lower bounds such as 336 for A(64, 12, 8), etc. (listed in Table 2). To obtain these results, we have developed a new systematic technique for construction by means of groups acting on some sets. The new technique is performed by considering a triad (G, Ω, f) := ("Group G," "Set Ω," "Action f on Ω") simultaneously. Our results described in Sect. 3 are obtained by using permutations of the elements of a set that include ∞ homogeneously like the other elements, which play a role to improve their randomness. Specifically, in our examples, we adopt the following model such as (PGL2(Fq), P1(Fq), "linear fractional action of subgroups of PGL2(Fq) on P1(Fq)") as a typical construction model. Moreover, as an application, the essential examples in [7] constructed by using an alternating group are again reconstructed with our new technique of a triad model, after which they are all systematically understood in the context of finite subgroups that act fractionally on a projective space over a finite field.

In this paper, a multistage parallel interference canceller (MPIC) with multiple-beam reception for a DS-CDMA system is proposed to suppress multiple access interference (MAI) effectively. Its aim is to reduce the computational complexity of the conventional MPIC cascaded with an adaptive array antenna. It employs multiple fixed beams based on phased array and selects suitable beams to demodulate the transmitted signal of each user. Then it suppresses residual interference signals by the MPIC cascaded with multiple-beam receiver. Its bit error rate (BER) performance is evaluated by computer simulations assuming an uplink single-chip-rate multiple-spreading-factor DS-CDMA system over both exponentially decaying 5-path and equal average power 2-path Rayleigh distributed channels. When there are 16 users in an 120-sectored single cell, the proposed receiver with 6-element array antenna and 2-stage MPIC shows better or comparable BER performance compared with that of the conventional receiver. Moreover, the proposed receiver with 8 beams can reduce the number of complex multiplications to about 40% of that of the complexity-reduced conventional receiver over 5-path channels.

We have researched high dimensional parity-check (HDPC) codes that give good performance over a channel that has a very high error rate. HDPC code has a little coding overhead because of its simple structure. It has hard-in, maximum detected bit flipping (MDBF) decoding that has reasonable decoding performance and computational cost. In this paper, we propose a modified algorithm for MDBF decoding and compare the proposed MDBF decoding with conventional hard-in decoding.

In this article, the security of double-block-length hash functions with the rate 1 is analyzed, whose compression functions are composed of block ciphers with their key length twice larger than their block length. First, the analysis by Satoh, Haga and Kurosawa is investigated, and it is shown that there exists a case uncovered by their analysis. Second, a large class of compression functions are defined, and it is shown that they are at most as secure as those of single-block-length hash functions. Finally, some candidate hash functions are given which are possibly optimally collision-resistant.

The notion of correlation intractable function ensembles (CIFEs) was introduced in an attempt to capture the "unpredictability" property of random oracles [12]: If O is a random oracle then it is infeasible to find an input x such that the input-output pair (x,O(x)) has some desired property. In this paper, we observe relationships between zero-knowledge protocols and CIFEs. Specifically, we show that, in the non-uniform model, the existence of CIFEs implies that 3-round auxiliary-input zero-knowledge (AIZK) AM interactive proofs exist only for BPP languages. In the uniform model, we show that 3-round AIZK AM interactive proofs with perfect completeness exist only for easy-to-approximate languages. These conditional triviality results extend to constant-round AIZK AM interactive proofs assuming the existence of multi-input CIFEs, where "multi-input" means that the correlation intractability is satisfied with respect to multiple input-output pairs. Also, as a corollary, we show that any construction of uniform multi-input CIFEs from uniform one-way functions proves unconditionally that constant-round AIZK AM interactive proofs with perfect completeness only for easy-to-approximate languages.

Recently, lattice reduction aided (LRA) detectors have been introduced into Vertical Bell-Labs Layered Space-Time (V-BLAST) systems to obtain nearly optimal bit error rate (BER) performance for only small additional complexity. In this paper, the layer error characteristics of LRA-V-BLAST detectors are investigated and compared with those of conventional V-BLAST ones. Two important conclusions are drawn for the LRA-V-BLAST detectors. First, the variation of their mean square error (MSE) within each detection iteration is not as large as in conventional V-BLAST detectors. Second, thanks to lattice reduction there exists an inherent sub-optimal detection order from the last to the first layer. These conclusions allow LRA-V-BLAST detectors to avoid optimal ordering to further reduce the complexity. LRA-V-BLAST detectors without optimal ordering are shown to obtain almost the same BER performance of LRA-V-BLAST detector with optimal ordering.

In this paper, we propose a method to estimate affine motion parameters from consecutive images with the assumption that the motion in progress can be characterized by an affine model. The motion may be caused either by a moving camera or moving object. The proposed method first extracts motion vectors from a sequence of images and then processes them by adaptive robust estimation to obtain affine parameters. Typically, a robust estimation filters out outliers (velocity vectors that do not fit into the model) by fitting velocity vectors to a predefined model. To filter out potential outliers, our adaptive robust estimation defines a flexible weight function based on a sigmoid function. During the estimation process, we tune the sigmoid function gradually to its hard-limit as the errors between the input data and the estimation model are decreased, so that we can effectively separate non-outliers from outliers with the help of the finally tuned hard-limit form of the weight function. The experimental results show that the suggested approach is very effective in estimating affine parameters.

In this paper, we present a new low-cost concurrent error detection (CED) S-Box architecture for the Advanced Encryption Standard (AES). Because the complexity and the nonlinearity, it is difficult to develop error detection algorithms for the S-Box. Conventionally, a parity checked S-Box is implemented with ROM (read only memory). In some applications, for example, smart cards, both chip size and fault detection are demanded seriously. ROM-based parity checking cannot meet the demands. We propose our CED S-Box (CEDSB) architecture for two reasons. The first is to design a S-Box without ROM. The second is to obtain a compact S-Box with real time error detection. Based on the composite field, we develop the CEDSB architecture to implement the fault detection for the S-Box. The overhead of the CED for the S-Boxes in GF((24)2) and in GF(((22)2)2) are 152 and 132 NAND gates respectively. The amount of extra gates used for the CEDSB is nearly equal to that of the ROM-based CED S-Box (131 NAND gates). The chip area of the ROM-based CED S-Box, the CEDSBs in GF((24)2), and in GF(((22)2)2) are 2996, 558, and 492 NAND gates separately. The chip area of the CEDSB is more compact than a ROM-based CED S-Box.

If some differences of perceptions arise between populations, then strategies which are regarded as the same strategy in a population may be perceived distinguishably in the other populations. To discuss such a situation, replicator dynamics for multi-population hypergames has been proposed. However, it is assumed that players' perceptions are given and fixed. In this paper, we consider that each population has various interpretation functions and choose one of them depending on payoffs, and we propose a hybrid system representation of replicator dynamics with changes of interpretation functions. Moreover, we apply our proposed model to a well-known example of a hypergame "Soccer Hooliganism" and show that behaviors converging to heteroclinic orbits can appear by the changes of the interpretation functions.

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.

A novel method to simplify decision functions of support vector machines (SVMs) is proposed in this paper. In our method, a decision function is determined first in a usual way by using all training samples. Next those support vectors which contribute less to the decision function are excluded from the training samples. Finally a new decision function is obtained by using the remaining samples. Experimental results show that the proposed method can effectively simplify decision functions of SVMs without reducing the generalization capability.

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.