In this paper, a novel independent component analysis (ICA) approach is proposed, which is robust against the interference of impulse noise. To implement ICA in a noisy environment is a difficult problem, in which traditional ICA may lead to poor results. We propose a method that consists of noise detection and image signal recovery. The proposed approach includes two procedures. In the first procedure, we introduce a self-organizing map (SOM) network to determine if the observed image pixels are corrupted by noise. We will mark each pixel to distinguish normal and corrupted ones. In the second procedure, we use one of two traditional ICA algorithms (fixed-point algorithm and Gaussian moments-based fixed-point algorithm) to separate the images. The fixed-point algorithm is proposed for general ICA model in which there is no noise interference. The Gaussian moments-based fixed-point algorithm is robust to noise interference. Therefore, according to the mark of image pixel, we choose the fixed-point or the Gaussian moments-based fixed-point algorithm to update the separation matrix. The proposed approach has the capacity not only to recover the mixed images, but also to reduce noise from observed images. The simulation results and analysis show that the proposed approach is suitable for practical unsupervised separation problem.

This paper presents a method for blind identification of a system whose transfer matrix is non-invertible at infinity, based on independent component analysis. In the proposed scheme, the transfer matrix to be identified is pre-multiplied by an appropriate polynomial matrix, named interactor, in order to compensate the row relative degrees and obtain a biproper system. It is then pre-multiplied by a demixing matrix via an existing approximate method. Both of these matrices are estimated blindly, i.e. with the input signals being unknown. The identified system is thus obtained as the inverse of the multiplication of these matrices.

Gains of a roll force AGC (Automatic Gain Controller) have been calculated at the first locked-on-time by FSU (Finishing-mill Set-Up model) in hot strip mills and usually these values are not adjusted during the operating time. Consequently, this conventional scheme cannot cope with the continuous variation of system parameters and circumstance, though the gains can be changed manually with the aid of experts to prevent a serious situation such as inferior mass production. Hence, partially uncontrolled variation still remains on delivery thickness. This paper discusses an effective online algorithm which can adjust the gains of the existing control system by considering the effect of time varying variables. This algorithm improves the performance of the system without additional cost and guarantees the stability of the conventional system. Specifically, this paper reveals the major factors that cause the variation of strip and explores the relationship between AGC gains and the effects of those factors through the analysis of thickness signal which occupy different frequency bands. The proposed tuning algorithm is based on the above relationship and realized through ANFIS (Adaptive-Neuro-based Fuzzy Interface System) which is a very useful method because its fuzzy logics reflect the experiences of professionals about the uncertainty and the nonlinearity of the system. The effectiveness of the algorithm is shown by several simulations which are carried out by using the field data of POSCO corporation (South Korea).

In real-time systems, deadline misses of the tasks cause a degradation in the quality of their results. To improve the quality, we have to allocate CPU utilization for each task adaptively. Recently, Buttazzo et al. address a feedback scheduling algorithm, which dynamically adjusts task periods based on the current workloads by applying a linear elastic task model. In their model, the utilization allocated to each task is treated as the length of a linear spring and its flexibility is described by a constant elastic coefficient. In this paper, we first consider a nonlinear elastic task model, where the elastic coefficient depends on the utilization allocated to the task. We propose a simple iterative method for calculating the desired allocated resource and derive a sufficient condition for the convergence of the method. Next, we apply the nonlinear elastic model to an adaptive fair sharing controller. Finally, we show the effectiveness of the proposed method by computer simulation.

This paper studies nonlinear dynamics of a simplified model of multiple-input parallel buck converters. The dynamic winner-take-all switching is used to achieve N-phase synchronization automatically, however, as parameters vary, the synchronization bifurcates to a variety of periodic/chaotic phenomena. In order to analyze system dynamics we adopt a simple piecewise constant modeling, extract essential parameters in a dimensionless circuit equation and derive a hybrid return map. We then investigate typical bifurcation phenomena relating to N-phase synchronization, hyperchaos, complicated superstable behavior and so on. Ripple characteristics are also investigated.

Data detection based on self organizing maps is presented for hematopoietic tumor patients. Learning data for the maps are generated from the screening data of examinees. The incomplete screening data without some item values is then supplemented by substituting averaged non-missing item values. In addition, redundant items, which are common to all the data and tend to have an unfavorable influence on data detection, are eliminated by a genetic algorithm and/or an immune algorithm. It is basically judged, by observing the label of a winner neuron in the map, whether the data presented to the map belongs to the class of hematopoietic tumors. Some experimental results are provided to show that the proposed methods achieve the high probability of correctly identifying examinees as hematopoietic tumor patients.

In this paper, we propose two 2's-complement fixed-width Booth multipliers that can generate an n-bit product from an n-bit multiplicand and an n-bit multiplier. Compared with previous designs, our multipliers have smaller truncation error, less area, and smaller time delay in the critical paths. A four-step approach is adopted to search for the best error-compensation bias in designing a multiplier suitable for VLSI implementation. Last but not least, we show the superior capability of our designs by inscribing it in a speech signal processor. Simulation results indicate that this novel design surpasses the previous fixed-width Booth multiplier in the precision of the product. An average error reduction of 65-84% compared with a direct-truncation fixed-width multiplier is achieved by adding only a few logic gates.

Grey model (abbreviated as GM), which is based on Deng's grey theory, has been established as a prediction model. At present, it has been widely applied in many research fields to solve efficiently the predicted problems of uncertainty systems. However, this model has irrational problems concerning the calculation of derivative and background value z since the predicted accuracy of GM is unsatisfying when original data shows great randomness. In particular, the predicted accuracy falls in case of higher-order derivative or multivariate greatly. In this paper, the new calculation methods of derivative and background value z are first proposed to enhance the predicted power according to cubic spline function. The newly generated model is defined as 3spGM. To further improve predicted accuracy, Taylor approximation method is then applied to 3spGM model. We call the improved version as T-3spGM. Finally, the effectiveness of the proposed model is validated with three real cases.

List decoding is a process by which a list of decoded words is output instead of one. This works for a larger noise threshold than the traditional algorithms. Under some circumstances it becomes useful to be able to find out the actual message from the list. List decoding is assumed to be successful, meaning, the sent message features in the decoded list. This problem has been considered by Guruswami. In Guruswami's work, this disambiguation is done by sending supplementary information through a costly, error-free channel. The model is meaningful only if the number of bits of side information required is much less than the message size. But using deterministic schemes one has to essentially send the entire message through the error free channel. Randomized strategies for both sender and receiver reduces the required number of bits of side information drastically. In Guruswami's work, a Reed-Solomon code based hash family is used to construct such randomized schemes. The scheme with probability utmost ε reports failure and returns the whole list. The scheme doesn't output a wrong message. Also, in Guruswami's work some theoretical bounds have been proved which lower bound the bits of side information required. Here we examine whether the gap between the theoretical bounds and existing schemes may be narrowed. Particularly, we use the same scheme as in Guruswami's work, but use hash families based on Hermitian curve and function fields of Garcia-Stichtenoth tower and analyze the number of bits of side information required for the scheme.

Convolutional spreading CDMA with cyclic prefix (CS-CDMA/CP) is a multiuser interference-free (MUI-free) CDMA scheme proposed for multipath channels based on the convolution between user data and zero correlation zone (ZCZ) code, and its characteristics depend on the employed ZCZ codes. Although ternary ZCZ codes have more sequences than binary ZCZ codes in general, transmitted signal with ternary ZCZ codes give a slightly higher peak-to-average power ratio (PAPR). In this paper we propose the use of periodic ZCZ codes generated from an M-sequence which not only provides the same user capacity as ternary ZCZ codes but allows more design flexibility. Simulation results show that the new ZCZ code shows stronger robustness against an imperfect transmitter with clipping and enjoys better BER performances when used in CS-CDMA/CP compared to the conventional DS-CDMA with MRC-RAKE.

Soft-decision decoding techniques are applied to asynchronous frequency-hop/spread-spectrum multiple-access (FH/SSMA) networks, where M-ary frequency shift keying (MFSK) is employed to transmit one modulated symbol per hop. Coding schemes using soft-decision decoded binary convolutional codes or turbo codes are considered, both with or without bit-interleaving. Performances of several soft metrics are examined for each coding scheme. It is shown that when multiple access interference is the main source of errors, the product metric offers the best performance among the soft metrics considered for all coding schemes. Furthermore, the application of soft-decision decoded convolutional codes or turbo codes without bit-interleaving is shown to allow for a much larger number of simultaneously transmitting users than hard-decision decoded Reed-Solomon codes. Finally, it is observed that when soft-decision decoding techniques are employed, synchronous networks attain better performance than asynchronous networks.

The design of the finite impulse response (FIR) notch filter with controlled null width is expressed as a derivatively contrained quadratic optimization problem. The problem is transformed into an unconstrained one by choosing a null matrix orthogonal to the derivative constraint matrix. In this paper, subband decomposition using wavelet filters is employed to construct the null matrix. Taking advantage of the vanishing moment property of the wavelet filters, the proposed method can adjust the null width of the notch filter for eliminating the intractable iterference by controlling the regularity of the wavelet filters. Simulation results show that the new method can offer comparable performance as those of the existing full-rank-based ones and thus provides a promising alternative to the existing works.

In this paper, we present a directional interpolation filter in which the minimum and maximum pixels in the given window are excluded. Image pixels within a predefined window are ranked and classified as minimum-maximum or exclusive level, and then passed through the interpolation and identity filters, respectively. Extensive simulations show that the proposed filter performs better than other nonlinear filters in preserving desired image features while reducing impulse noise effectively.

To design a controller with block-diagonal structure for trajectory sensitivity minimization, we propose a method based on LMI. In order to reduce the trajectory sensitivity, linear quadratic regulator theory is adopted, and this is solved using LMI optimization technique.

The extened Kalman filter (EKF) and unscented Kalman filter (UKF) have been successively applied in particle filter framework to generate proposal distributions, and shown significantly improving performance of the generic particle filter that uses transition prior, i.e., the system state transition prior distribution, as the proposal distribution. In this paper we propose to use the Gauss-Newton EKF/UKF to replace EKF/UKF for generating proposal distribution in a particle filter. The Gauss-Newton EKF/UKF that uses iterated measurement update can approximate the optimal proposal distribution more closer than EKF/UKF, especially in the case of significant nonlinearity in the measurement function. As a result, the Gauss-Newton EKF/UKF is able to generate and propagate the proposal distribution for each particle much better than EKF/UKF, thus further improving the performance of state estimation. Simulation results for a nonlinear/non-Gaussian time-series demonstrate the superior estimation accuracy of our method compared with state-of-the-art filters.

The realization of k-nearest-matches search capability in fully-parallel mixed digital-analog associative memories by a sequential autonomous search mode is reported. The proposed concept and circuit implementation can be applied with all types of distance measures such as Hamming, Manhattan or Euclidean distance search, and the k value can be freely selected during operation. A test chip for concept verification has been designed in 0.35 µm CMOS technology with two-poly, three-metal layers, realizes k-nearest-matches Euclidean distance search and consumes 5.12 mm² of the chip area for 64 reference patterns each with 16 units of 5-bit.

A new quadruple watermarking scheme of digital images against geometrical attacks is proposed in this letter. We treat the center and the four vertexes of the original image as the reference points and embed the same quadruple watermarks by means of polar coordinates, which is geometrically invariant. The center of an image is assumed to not to be removed after rotating, scaling and local distortions according to the general practical image processing. In the watermark extraction process, the vertexes of the image are found by a searching method. Thus watermark synchronization is obtained. Experimental results show that the scheme is robust to the geometrical distortions including rotation, scaling, cropping and local distortions.

This letter yields a security evaluation of certain broadcast encryption (BE) schemes regarding the generic vulnerability of the textbook BE schemes. The considered vulnerability can be effectively explored assuming known plaintext attacks which in a realistic scenario, corresponding to a legitimate user being the attacker, appears as a ciphertext only attack. Employing the birthday paradox, a dedicated time-data trade-off based algorithm for cryptanalysis is proposed. The developed algorithm is applied to cryptanalysis of particular recently reported class of BE schemes, implying additional insights regarding motivations for their security improvements.

This letter proposes a simple combined coding and modulation based on super-orthogonal convolutional codes (SOCs) in order to support both coherent and non-coherent ultra-wideband (UWB) receivers. In the proposed scheme, the coherent receivers obtain a coding gain as large as the SOC while simultaneously supporting non-coherent receivers. In addition, their performance can be freely adapted by changing the encoder constraint length and the number of PPM slots according to its application. Thus, the proposal enables a more flexible system design for low data-rate UWB systems.