This letter presents delayed perturbation bounds (DPBs) for receding horizon controls (RHCs) of continuous-time systems. The proposed DPBs are obtained easily by solving convex problems represented by linear matrix inequalities (LMIs). We show, by numerical examples, that the RHCs have larger DPBs than conventional linear quadratic regulators (LQRs).

This paper reports a novel design in Photonic Crystal Fibers (PCFs) with nearly zero ultra-flattened dispersion characteristics. We describe the chromatic dispersion controllability taking non-uniform air hole structures into consideration. Through optimizing non-uniform air hole structures, the ultra-flattened zero dispersion PCFs can be efficiently designed. We show numerically that the proposed non-uniform air cladding structures successfully archive flat dispersion characteristics as well as extremely low confinement losses. As an example, the proposed PCF with flattened dispersion of 0.27 ps/(nmkm) from 1.5 µm to 1.8 µm wavelength with confinement losses of less than 10-11 dB/m. Finally, we point out that full controllability of the chromatic dispersion and confinement losses, along with the fabrication technique, are the main advantages of the proposed PCF structure.

A reversible data hiding scheme based on the companding technique and the difference expansion (DE) of triplets is proposed in this paper. The companding technique is employed to increase the number of the expandable triplets. The capacity consumed by the location map recording the expanded positions is largely decreased. As a result, the hiding capacity is considerably increased. The experimental results reveal that high hiding capacity can be achieved at low embedding distortion.

This paper proposes a new adaptive filter algorithm for system identification by using an independent component analysis (ICA) technique, which separates the signal from noisy observation under the assumption that the signal and noise are independent. We first introduce an augmented state-space expression of the observed signal, representing the problem in terms of ICA. By using a nonparametric Parzen window density estimator and the stochastic information gradient, we derive an adaptive algorithm to separate the noise from the signal. The proposed ICA-based algorithm does not suppress the noise in the least mean square sense but to maximize the independence between the signal part and the noise. The computational complexity of the proposed algorithm is compared with that of the standard NLMS algorithm. The stationary point of the proposed algorithm is analyzed by using an averaging method. We can directly use the new ICA-based algorithm in an acoustic echo canceller without double-talk detector. Some simulation results are carried out to show the superiority of our ICA method to the conventional NLMS algorithm.

The article describes recent adaptive estimation algorithms over distributed networks. The algorithms rely on local collaborations and exploit the space-time structure of the data. Each node is allowed to communicate with its neighbors in order to exploit the spatial dimension, while it also evolves locally to account for the time dimension. Algorithms of the least-mean-squares and least-squares types are described. Both incremental and diffusion strategies are considered.

A new framework for reconstruction of missing textures in digital images is introduced in this paper. The framework is based on a projection onto convex sets (POCS) algorithm including a novel constraint. In the proposed method, a nonlinear eigenspace of each cluster obtained by classification of known textures within the target image is applied to the constraint. The main advantage of this approach is that the eigenspace can approximate the textures classified into the same cluster in the least-squares sense. Furthermore, by monitoring the errors converged by the POCS algorithm, a selection of the optimal cluster to reconstruct the target texture including missing intensities can be achieved. This POCS-based approach provides a solution to the problem in traditional methods of not being able to perform the selection of the optimal cluster due to the missing intensities within the target texture. Consequently, all of the missing textures are successfully reconstructed by the selected cluster's eigenspaces which correctly approximate the same kinds of textures. Experimental results show subjective and quantitative improvement of the proposed reconstruction technique over previously reported reconstruction techniques.

A fast intra-mode decision algorithm is proposed on the basis of an inter-mode block type for inter-frames (P-slices). Each macroblock (MB) type has its own intra prediction modes (I16MB and 88 chroma: 4 modes, I4MB and I8MB: 9 modes). This procedure creates a large computational complexity in addition to the inter mode decision procedure. In most cases, there is a high correlation between the best inter-mode block type and the direction of the texture edge or object boundary. Therefore, only a small number of intra-prediction modes are chosen to determine the best intra mode based on this correlation. We experimentally verify that the proposed scheme can significantly improve the speed of the overall encoding time with a negligible loss of image quality and a minimal bit increase. The average loss in PSNR was -0.0120.036 dB and the bit increment was approximately -0.1940.751%.

Orthogonal frequency division multiplexing (OFDM) is an attractive technique to accomplish wired or wireless broadband communications. Since it has been adopted as the terrestrial digital-video-broadcasting standard in Europe, it has also subsequently been embedded into many broadband communication standards. Many techniques for frame timing and frequency synchronization of OFDM systems have been studied as a result of its increasing importance. We propose a new technique of simultaneously synchronizing frame timing and frequency utilizing matched filters. First, a new short preamble consisting of short sequences multiplied by a DBPSK coded sequence is proposed. Second, we show that the new short preamble results in a new structure for matched filters consisting of a first matched filter, a DBPSK decoder, and a second matched filter. We can avoid the adverse effects of carrier frequency offset (CFO) when frame timing is synchronized because a DBPSK decoder has been deployed between the first and second matched filters. In addition, we show that the CFO can be directly estimated from the peak value of matched filter output. Finally, our simulation results demonstrate that the proposed scheme outperforms the conventional schemes.

In this paper, we propose a novel bicubic method for digital image interpolation. Since the conventional bicubic method does not consider image local features, the interpolated images obtained by the conventional bicubic method often have a blurring problem. In this paper, the proposed bicubic method adopts both the local asymmetry features and the local gradient features of an image in the interpolation processing. Experimental results show that the proposed method can obtain high accuracy interpolated images.

The long-term bit error rate (BER) performance of partial response maximum likelihood (PRML) system using an adaptive equalizer in a perpendicular magnetic recording (PMR) channel with thermal decay is studied. A thermal decay model based on the experimental data giving the amplitude change of reproducing waveforms with the elapsed time for CoPtCr-SiO2 PMR medium is obtained. The BER performance of PR1ML channel for the 16/17(0,6/6) run-length-limited (RLL) code is evaluated by computer simulation using the model. The relationship between the ratio RJ of the jitter-like media noise power to the total noise power at the reading point and the required SNR to achieve a BER of 10-4 is also obtained and the performance is compared with that of the conventional equalization. The results show that the significant improvement in SNR by utilizing the adaptive equalization is recognized over all RJ compared with the conventional equalization.

The performance of TCP data transmission deteriorates significantly when a TCP connection traverses a heterogeneous network consisting of wired and wireless links. This is mainly because of packet losses caused by the high bit error rate of wireless links. We proposed receiver-based ACK splitting mechanism in [1]. It is a new mechanism to improve the performance of TCP over wired and wireless heterogeneous networks. Our mechanism employs a receiver-based approach, which does not need modifications to be made to the sender TCP or the base station. It uses the ACK-splitting method for increasing the congestion window size quickly in order to restrain the throughput degradation caused by packet losses due to the high bit error rate of wireless links. In this paper, we develop a mathematical analysis method to derive the throughput of a TCP connection, with/without our mechanism, which traverses wired and wireless heterogeneous networks. By using the analysis results, we evaluate the effectiveness of our mechanism in the network where both of packet losses due to network congestion and those caused by the high bit error rate of wireless links take place. Through An evaluation of the proposed method shows that it can give a good estimation of TCP throughput under the mixture networks of wired/wireless links. We also find that the larger the bandwidth of the wireless link is, the more effective our mechanism becomes, therefore, the mechanism's usability will increase in the future as wireless networks become faster.

Several structured peer-to-peer networks have been created to solve the scalability problem of previous peer-to-peer systems such as Gnutella and Napster. These peer-to-peer networks which support distributed hash table functionality construct a sort of structured overlay network, which can cause a topology mismatch between the overlay and the underlying physical network. To solve this mismatch problem, we propose a topology-aware hierarchical overlay framework for DHTs. The hierarchical approach for the overlay is based on the concept that the underlying global Internet is also a hierarchical architecture, that is, a network of networks. This hierarchical approach for the overlay puts forth two benefits: finding data in a physically near place with a high probability, and smaller lookup time. Our hierarchical overlay framework is different from other hierarchical architecture systems in a sense that it provides a specific self-organizing grouping algorithm. Our additional optimization schemes complete the basic algorithm which constructs a hierarchical structure without any central control.

The class of complete complementary sequences (of fixed length) have the ideal correlation properties and are good at increasing the channel usage efficiency but lacks in desirable sequence lengths. In spread spectrum communication systems, sequences having nice correlation properties are important in many ways such as in suppressing multi-user interference, for reliable initial synchronization and in separation of the multipath components. It would be even good if the sequences are easy to construct and have desirable lengths for the system under consideration. In this paper, M sets of sequences that constitute a complete complementary sequences with ith set containing N sequences of length Li each, i = 0, 1, ..., M - 1, is defined and a general method that constructs such a class of complete complementary sequences (of different lengths) is given. The proposed class of complete complementary sequences, constituted by sequence sets of different lengths, does not increase the data rates when short-length sequences are employed.

We propose a robust iterative multiuser receiver for decoding convolutional coded code-division multiple access (CDMA) signals in both Gaussian and non-Gaussian channel noise. The receiver is derived from a modified maximum a-posteriori (MAP) algorithm called the max-log-MAP algorithm for robustness against erroneous channel variance estimation. Furthermore, the effect of destructive outliers arising from impulsive noise is mitigated in the proposed receiver by incorporating the robust Huber penalty function into the multiuser detector. The proposed receiver is shown to perform satisfactorily over Gaussian and non-Gaussian impulsive channels. In every iteration, cumulative improvement in the quality of the a-posteriori probabilities is also demonstrated.

A communication means is presented for patients with amyotrophic lateral sclerosis in totally locked-in state who are completely unable to move any part of the body and have no usual communication means. The method utilizes changes in cerebral blood volume accompanied with changes in brain activity. When a patient is asked a question and the answer to it is 'yes', the patient makes his or her brain active. The change in blood volume at the frontal lobe is detected with near-infrared light. The instantaneous amplitude and phase of the change are calculated, and the maximum amplitude and phase change are obtained. The answer 'yes' or 'no' of the patient is detected using a discriminant analysis with these two quantities as variables. The rate of correct detection is 80% on average.

Recent theoretical and experimental studies indicate that spatial multiplexing (SM) systems have enormous potential for increasing the capacity of corresponding multiple input multiple output (MIMO) channels in rich scattering environments. In this paper, we propose a new recursion based algorithm for Bell Labs layered space time (BLAST) signal detection in SM systems. The new algorithm uses an inflated recursion in the initialization and a deflated recursion in the iteration stage: as a result, the complexity is greatly reduced and the irregularity issues are completely avoided. Compared with the conventional fastest recursive approach, the complexity of our proposal is lower by a factor of 2 and it is also very implementation friendly.

Orthogonal frequency division multiplexing (OFDM) is one of the promising transmission techniques for next generation mobile communication systems. Accurate channel estimation is essential for coherent OFDM signal transmission. So far, many pilot-assisted channel estimation schemes have been proposed. In the case of packet transmission, each received packet can be repeatedly processed by decision feedback to improve the channel estimation accuracy, resulting in a decision directed block iterative channel estimation (DD-BICE). However, decision feedback of erroneously detected data symbols degrades the packet error rate (PER) or bit error rate (BER) performance. In this paper, theoretical analysis is presented for the DD-BICE taking into account the decision feedback errors assuming quadrature phase shift keying (QPSK) data modulation. A 2-dimensional (2D) averaging filter is used for reducing the negative impact of decision feedback errors. The impacts of 2D averaging filter and antenna diversity reception are discussed and the validity of the theoretical analysis is confirmed by computer simulation.

The subspace algorithm can be utilized for the blind detection of space-time block codes (STBC) without knowledge of channel state information (CSI) both at the transmitter and receiver. However, its performance degrades when the channels are correlated. In this letter, we analyze the impact of channel correlation from the orthogonality loss between the transmit signal subspace (TSS) and the statistical noise subspace (SNS). Based on the decoding property of the subspace algorithm, we propose a revised detection in favor of the channel correlation matrix (CCM) only known to the receiver. Then, a joint transmit-receive preprocessing scheme is derived to obtain a further performance improvement when the CCM is available both at the transmitter and receiver. Analysis and simulation results indicate that the proposed methods can significantly improve the blind detection performance of STBC over the correlated channels.

We developed a comprehensive simulation system for evaluating satellite-based navigation services in highly built-up areas; the system can accommodate Global Positioning System (GPS) multipath effects, as well as line-of-sight (LOS) and dilution of position (DOP) issues. For a more realistic simulation covering multipath and diffracted signal propagations, a 3D-ray tracing method was combined with a satellite orbit model and three-dimensional (3D) geographic information system (GIS) model. An accuracy estimation model based on a 3D position determination algorithm with a theoretical delay-locked loop (DLL) correlation computation could measure the extent to which multipath mitigation improved positioning accuracy in highly built-up areas. This system could even capture the multipath effect from an invisible satellite, one of the greatest factors in accuracy deterioration in highly built-up areas. Further, the simulation results of satellite visibility, DOP, and multipath occurrence were mapped to show the spatial distribution of GPS availability. By using object-oriented programming, our simulation system can be extended to other global navigation satellite systems (GNSSs) simply by adding the orbital information of the corresponding GNSS satellites. We demonstrated the applicability of our simulation system in an experimental simulation for Shinjuku, an area of Tokyo filled with skyscrapers.

We propose a new genetic fuzzy discretization method with feature selection for the pattern classification problems. Traditional discretization methods categorize a continuous attribute into a number of bins. Because they are made on crisp discretization, there exists considerable information loss. Fuzzy discretization allows overlapping intervals and reflects linguistic classification. However, the number of intervals, the boundaries of intervals, and the degrees of overlapping are intractable to get optimized and a discretization process increases the total amount of data being transformed. We use a genetic algorithm with feature selection not only to optimize these parameters but also to reduce the amount of transformed data by filtering the unconcerned attributes. Experimental results showed considerable improvement on the classification accuracy over a crisp discretization and a typical fuzzy discretization with feature selection.