In this study, we propose a robust approach for blind source separation (BSS) by using radial basis function networks (RBFNs) and higher-order statistics (HOS). The RBFN is employed to estimate the inverse of a hypothetical complicated mixing procedure. It transforms the observed signals into high-dimensional space, in which one can simply separate the transformed signals by using a cost function. Recently, Tan et al. proposed a nonlinear BSS method, in which higher-order moments between source signals and observations are matched in the cost function. However, it has a strict restriction that it requires the higher-order statistics of sources to be known. We propose a cost function that consists of higher-order cumulants and the second-order moment of signals to remove the constraint. The proposed approach has the capacity of not only recovering the complicated mixed signals, but also reducing noise from observed signals. Simulation results demonstrate the validity of the proposed approach. Moreover, a result of application to X-ray image separation also shows its practical applicability.

We propose a likelihood detection scheme that utilizes ordering and decision of partial bits in MIMO spatial multiplexing systems. We compute BER performance of the proposed detection scheme under Rayleigh fading channels in a 33 MIMO spatial multiplexing system and compare it with BER performance using MLD only and detection utilizing ZF or MMSE only. In addition, the computational complexity of the proposed detection scheme is compared with that of MLD and detection utilizing ZF or MMSE. The results of our investigation show that the proposed detection is a scheme achieves both good BER performance and low computational complexity.

We propose two sequence design schemes for an overloaded space-time spreading system with multiple antennas. One scheme is for a system in which the amplitude of user signals needs not be adjusted and provides tradeoffs between the user capacity and diversity order. This scheme has a certain similarity to time-sharing, but its performance is further improved by time-diversity. Another is to achieve full diversity order by varying user signal amplitudes. The diversity orders of the respective schemes are theoretically proved and their performances are demonstrated by simulation.

This study shows the effectiveness of using gamma distribution in the speech power domain as a more general prior distribution for the model-based speech enhancement approaches. This model is a super-set of the conventional Gaussian model of the complex spectrum and provides more accurate prior modeling when the optimal parameters are estimated. We develop a method to adapt the modeled distribution parameters from each actual noisy speech in a frame-by-frame manner. Next, we derive and investigate the minimum mean square error (MMSE) and maximum a posterior probability (MAP) estimations in different domains of speech spectral magnitude, generalized power and its logarithm, using the proposed gamma modeling. Finally, a comparative evaluation of the MAP and MMSE filters is conducted. As the MMSE estimations tend to more complicated using more general prior distributions, the MAP estimations are given in closed-form extractions and therefore are suitable in the implementation. The adaptive estimation of the modeled distribution parameters provides more accurate prior modeling and this is the principal merit of the proposed method and the reason for the better performance. From the experiments, the MAP estimation is recommended due to its high efficiency and low complexity. Among the MAP based systems, the estimation in log-magnitude domain is shown to be the best for the speech recognition as the estimation in power domain is superior for the noise reduction.

In this letter, a phase noise reduction algorithm for orthogonal frequency division multiplexing (OFDM) systems with an input of higher-order constellation is proposed to achieve high data rate transmission. The proposed algorithm estimates dominant interchannel interference (ICI) terms, caused by phase noise, using the subcarriers adjacent to pilot subcarriers, and compensates the OFDM signal using these estimates. Also, the length of dominant ICI terms is efficiently determined by estimating 3 dB bandwidth of phase noise. The proposed algorithm is shown to reduce the effect of phase noise on OFDM systems with an input of higher-order modulation and a large amount of phase noise.

This work proposes a new method for RLCG interconnect model-order reductions in consideration with the adjoint network. Relationships between an original MNA network and its corresponding adjoint MNA network will be explored first. It will be shown that the congruence transformation matrix used in the one-sided projection can be constructed by using the bi-orthogonal bases developed from the Lanczos-type algorithms. In particular, if the multi-port driving-point impedance of RLCG interconnect circuits is the main concern, the transfer functions and system moments of the adjoint network can be directly calculated from those of the original RLCG interconnect network by exploring symmetric properties of the MNA formulation. Therefore, the cost of constructing the congruence transformation matrix can be simplified by up to 50% of the previous methods. Comparative studies among various standard methods and the proposed methods are also investigated. Experimental results on large-scale RLCG interconnect circuits will demonstrate the accuracy and the efficiency of the proposed method.

Irregular Low-Density Parity-Check (LDPC) codes generally achieve better performance than regular LDPC codes at low Eb/N0 values. They have, however, higher error floors than regular LDPC codes. With respect to the construction of the irregular LDPC code, it can achieve the trade-off between the performance degradation of low Eb/N0 region and lowering error floor. It is known that a decoding algorithm can achieve very good performance if it combines the Ordered Statistic Decoding (OSD) algorithm and the Log Likelihood Ratio-Belief Propagation (LLR-BP) decoding algorithm. Unfortunately, all the codewords obtained by the OSD algorithm satisfy the parity check equation of the LDPC code. While we can not use the parity check equation of the LDPC code to stop the decoding process, the wrong codeword that satisfies the parity check equation raises the error floor. Once a codeword that satisfies the parity check equation is generated by the LLR-BP decoding algorithm, we regard that codeword as the final estimate and halt decoding; the OSD algorithm is not performed. In this paper, we propose a new encoding/decoding scheme to lower the error floor created by irregular LDPC codes. The proposed encoding scheme encodes information bits by Cyclic Redundancy Check (CRC) and LDPC code. The proposed decoding scheme, which consists of the LLR-BP decoding, CRC check, and OSD decoding, detects errors in the codewords obtained by the LLR-BP decoding algorithm and the OSD decoding algorithm using the parity check equations of LDPC codes and CRC. Computer simulations show that the proposed encoding/decoding scheme can lower the error floor of irregular LDPC codes.

There is redundancy in instruction sequences, which can be utilized for information hiding or digital watermarking. This study quantitatively examines the information capacity in the order of variables, basic blocks, and instructions in each basic block. Derived information density was 0.3% for reordering of basic blocks, 0.3% for reordering instructions in basic blocks, and 0.02% for reordering of global variables. The performance degradation caused by this method was less than 6.1%, and the increase in the object file size was less than 5.1%.

Gossip-based reliable broadcast protocols with reasonably weak reliability properties scale well to large groups and degrade system performance gracefully even if node failure or message loss rates increase compared with traditional protocols. However, although many distributed applications require highly steady performance only by allowing causality to be used asynchronously, there is no existing gossip-based protocol offering causally ordered delivery property more lightweight than totally ordered delivery one. This paper presents an application-level broadcast algorithm to guarantee causally-ordered delivery semantics based on peer to peer interaction models for scalability, reasonable reliability and stable throughput. Processes propagate each message with a vector time stamp much like the spread of rumor in society for a fixed number of rounds. Upon receipt of these messages, correct processes immediately deliver the corresponding messages to the application layers in a causal order. Simulation results show that the proposed algorithm outperforms the existing ones in terms of delivery throughput.

This paper describes a novel engineering change order (ECO) design method for large-scale, high performance LSIs, based on a patchwork-like partitioning technique. In conventional design methods, even when only small changes are made to the design after the placement and routing process, a whole re-layout must be done, and this is very time consuming. Using the proposed method, we can partition the design into several parts after logic synthesis. When design changes occur in HDL, only the parts related to the changes need to be redesigned. The netlist for the changed design remains almost the same as the original, except for the small changed parts. For partitioning, we used multiple-fan-out-points as partition borders. An experimental evaluation of our method showed that when a small change was made in the RTL description, the revised circuit part had only about 87 gates on average. This greatly reduces the re-layout time required for implementing an ECO. In actual commercial designs in which several design changes are required, it takes only one day to redesign.

In this letter, a new asynchronous Re-Order Buffer (ROB) with fully distributed control is proposed for an asynchronous on-chip bus. Due to the fully distributed control by each dedicated controller, the proposed ROB has high modularity and scalability. Simulation results show that the proposed asynchronous ROB can operate on an asynchronous on-chip bus of 2.01 Gbit/s throughput and 0.232 nJ power consumption per bus transaction.

This paper proposes a new detection ordering scheme, which minimizes average error rate of the MIMO system with per antenna rate control. This paper shows an optimal scheme minimizing average error rate expressed by the Q function, and simplifies the optimal scheme by using the minimum equivalent SINR scaled by modulation indices, based on approximated error rate. In spite of reduced complexity, the simplified scheme demonstrates the almost same performance as the optimal scheme. Owing to the diversity of detection ordering, the proposed scheme has over 2 dB higher SNR gain at the BER of 10-3 than the existing ordering schemes in balanced array size systems.

Document merging is essential to synchronizing several versions of a document concurrently edited by two or more users. A few methods for merging structured documents have been proposed so far, and yet the methods may not always merge given documents appropriately. As an aid for finding an appropriate merging, using another approach we propose a polynomial-time algorithm for merging structured documents. In the approach, we merge given two documents (treated as ordered trees) by optimally transforming the documents into isomorphic ones, using operations such as add (add a new node), del (delete an existing node), and upd (make two nodes have the same label).

Grid computing is a state-of-the-art parallel computing technology which enables worldwide computers to dynamically share their computing powers and resource to each other. The grid takes advantage of Internet as a universal communication platform to carry messages. Basically, Internet doesn't guarantee loss-free and ordered transmission, hence, the grid should keep the cause and effect of events by itself to ensure the correct ordering of command invocations at the remote hosts. The ordering issue arises when the messages travel across the networks with unpredictable delay. Recent research has studied the security and resource control issues, but failed to address the requirements of transport layer on the grid communication platform. In this paper, we propose the Causal Ordered Grid (COG) architecture and implement it to study the transport performance issues when the grid is built over worldwide networks. The COG provides a novel service model to the applications with time-sensitive and causal-ordered transportation. From our experiments, the design of the grid middleware should use a causal-ordered, time-sensitive transportation rather than TCP. Our research will be beneficial to the improvement of the grid computing and can provide wealthy empirical results for the designer.

The authors propose a system for searching the shape of human hands and fingers in real time and with high accuracy, without using any special peripheral equipment such as range sensor, PC cluster, etc., by a method of retrieving similar image quickly with high accuracy from a large volume of image database containing the complicated shapes and self-occlusions. In designing the system, we constructed a database in a way to be adaptable even to differences among individuals, and searched CG images of hand similar to unknown hand image, through extraction of characteristics using high-order local autocorrelational patterns, reduction of the amount of characteristics centering on principal component analysis, and prior rearrangement of data corresponding to the amount of characteristics. As a result of experiments, our system performed high-accuracy estimation of human hand shape where mean error was 7 degrees in finger joint angles, with the processing speed of 30 fps or over.

The bandwidth explosion ushered in by the popularity of the Internet has spurred the recent acceleration in the development and deployment of equipment supporting packet based broadband services. This coupled with the widespread deployment of WDM based Optical Transport Systems in the core network to satisfy the corresponding increase in capacity demand, has led network planners for tighter coordination between IP and Optical layers to increase reliability, robustness of next generation backbone network. In this paper, we propose a solution known as border model, which is tailored to address deployment concerns associated with GMPLS technology in existing networks. We extend our proposal to include, "Border model based Multi-layer service network architecture," to provide coordinated multi-layer IP and Optical services, for different network design scenarios. Resource Control is an important aspect of multi-layer service networks. This paper examines next generation requirements for resource control, defines resource control architecture and presents some evaluation results for multi-layer recovery techniques in the context of Multi-layer service network based on border model.

In this paper, we present a minimum-maximum exclusive weighted-mean filtering algorithm with adaptive window. Image pixels within the varying size of the window are ranked and classified as minimum-maximum and median levels, and then passed through the weighted-mean of median level and identity filters, respectively. The filtering window size is adaptively increasing according to noise ratio without noise measurement. Extensive simulations show that the proposed filter performs better than other median/rank-type filters in removing impulse noise of highly corrupted images.

In this paper we focus on the decoding error of the Log-Likelihood Ratio Belief Propagation (LLR-BP) decoding algorithm caused by oscillation. The decoding error caused by the oscillation is dominant in high Eb/N0 region. Oscillation of the LLR of the extrinsic value in the bit node process (ex-LLR) is propagated to the other bits and affects the whole decoding. The Ordered Statistic Decoding (OSD) algorithm is known to improve the error rate performance of the LLR-BP decoding algorithm. The OSD algorithm is performed by deciding the reliability of each bit based on a posteriori probability. In this paper we propose two decoding algorithms based on two types of oscillations of LLR for LDPC codes. One is the oscillation-based OSD algorithm with deciding the reliability of each bit based on oscillation. The other is the oscillation-based LLR-BP decoding algorithm that modifies ex-LLR based on oscillation. In the oscillation-based LLR-BP decoding algorithm, when ex-LLR oscillates, then we reduce the magnitude of this ex-LLR to reduce the effects on the other bits. Both algorithms improve the decoding errors caused by oscillation. From the computer simulations, we show that paying attention to the oscillation, we can improve the error rate performance of the LLR-BP decoding algorithm.

Visibility culling techniques have been studied extensively in computer graphics for interactive walkthrough applications in recent years. In this paper, a visibility culling approach by exploiting hardware-accelerated occlusion query is proposed. Organizing the regular grid representation of input scene as an octree-like hierarchy, a 2-tier view frustum culling algorithm is to efficiently cull away nodes invisible from a given viewpoint. Employing the eye-siding number of nodes, we can quickly enumerate an occlusion front-to-back order and effectively maximize the number of parallelizable occlusion queries for nodes while traversing the hierarchy. As experimental results show, our approach improves the overall performance in the test walkthrough.

We have proposed in [5] a practical blind channel identification algorithm for the white observation noise. In this paper, we examine the effectiveness of the algorithm given in [5] for the colored observation noise. The proposed algorithm utilizes Gram-Schmidt orthogonalization procedure and estimates (1) the channel order, (2) the noise variance and then (3) the channel impulse response with less computational complexity compared to the conventional algorithms using eigenvalue decomposition. It can be shown through numerical examples that the algorithm proposed in [5] is quite effective in the colored noise case.