This paper presents a VLSI architecture of MMSE detection in a 44 MIMO-OFDM receiver. Packet-based MIMO-OFDM imposes a considerable throughput requirement on the matrix inversion because of strict timing in frame structure and subcarrier-by-subcarrier basis processing. Pipeline processing oriented algorithms are preferable to tackle this issue. We propose a pipelined MMSE detector using Strassen's algorithms of matrix inversion and multiplication. This circuit achieves real-time operation which does not depend on numbers of subcarriers. The designed circuit has been implemented to a 90-nm CMOS process and shows a potential for providing a 2.6-Gbps transmission speed in a 160-MHz signal bandwidth.

A reversible watermark algorithm with large capacity has been developed by applying the difference expansion of a generalized integer transform. In this algorithm, a watermark signal is inserted in the LSB of the difference values among pixels. In this paper, we apply the prediction errors calculated by a predictor in JPEG-LS for embedding watermark, which contributes to increase the amount of embedded information with less degradation. As one of the drawbacks discovered in the above conventional method is the large size of the embedded location map introduced to make it reversible, we decrease the large size of the location map by vectorization, and then modify the composition of the map using the local characteristics. We also exclude the positions such that the modification in the embedding operation cannot increase the capacity but merely degrade the image quality, which can be applicable to the conventional methods.

The RFID (Radio Frequency IDentification) tag technology is expected as a tool of localization. By the localization of RFID tags, a mobile robot which installs in RFID readers can recognize surrounding environments. In addition, RFID tags can be applied to a navigation system for walkers. In this paper, we propose an adaptive likelihood distribution scheme for the localization of RFID tags. This method adjusts the likelihood distribution depending on the signal intensity from RFID tags. We carry out the performance evaluation of estimated position error by both computer simulations and implemental experiments. We show that the proposed system is more effective than the conventional system.

Configurable clock is necessary for many applications such as digital communication systems, however, using the conventional direct digital frequency synthesizer (DDS) as a pulse or clock generator may cause jitter problems. People usually employ phase-interpolation approaches to generate a pulse or clock with correct time intervals. This work proposes a new phase-interpolation DDS scheme, which uses the output of the phase accumulator to provide an initial voltage on an integration capacitor by pre-charging in the first phase, and then performs integration operation on the same integration capacitor in the second phase. By using single capacitor integration, the instability of the delay generator existed in the phase-interpolation DDS can be avoided, and the impact caused by capacitance error in the circuit implementation also can be reduced. Furthermore, without ROM tables, the proposed DDS using pre-charging integration not only reduces the spurious level of the clock output, but also has a low hardware complexity.

This investigation applies the adaptive fuzzy-neural observer (AFNO) to synchronize a class of unknown chaotic systems via scalar transmitting signal only. The proposed method can be used in synchronization if nonlinear chaotic systems can be transformed into the canonical form of Lur'e system type by the differential geometric method. In this approach, the adaptive fuzzy-neural network (FNN) in AFNO is adopted on line to model the nonlinear term in the transmitter. Additionally, the master's unknown states can be reconstructed from one transmitted state using observer design in the slave end. Synchronization is achieved when all states are observed. The utilized scheme can adaptively estimate the transmitter states on line, even if the transmitter is changed into another chaos system. On the other hand, the robustness of AFNO can be guaranteed with respect to the modeling error, and external bounded disturbance. Simulation results confirm that the AFNO design is valid for the application of chaos synchronization.

On the basis of the RF characteristics of p-type diamond field-effect transistors (FETs) with hydrogen surface termination, we establish an equivalent circuit (EQC) model. From comparisons of three cases we reveal that to represent the device performance in the EQC, the source, gate, and drain resistance should be considered but that the gate-source and gate-drain resistance can be ignored. The features of diamond FETs are (1) a plateau of the gate capacitance in a certain gate voltage range. (2) maximum fT and fMAX cut-off frequencies near the threshold gate voltage, and (3) a high fMAX/fT ratio 3.8. We discuss these features in terms of the energy barrier between the gate metal and the two-dimensional hole channel and drift region below the gate.

Using Bloom filters is one of the most popular and efficient lookup methods in P2P networks. A Bloom filter is a representation of data item indices, which achieves small memory requirement by allowing one-sided errors (false positive). In the lookup scheme besed on the Bloom filter, each peer disseminates a Bloom filter representing indices of the data items it owns in advance. Using the information of disseminated Bloom filters as a clue, each query can find a short path to its destination. In this paper, we propose an efficient extension of the Bloom filter, called a Deterministic Decay Bloom Filter (DDBF) and an index dissemination method based on it. While the index dissemination based on a standard Bloom filter suffers performance degradation by containing information of too many data items when its dissemination radius is large, the DDBF can circumvent such degradation by limiting information according to the distance between the filter holder and the items holders, i.e., a DDBF contains less information for faraway items and more information for nearby items. Interestingly, the construction of DDBFs requires no extra cost above that of standard filters. We also show by simulation that our method can achieve better lookup performance than existing ones.

An integrated power and rate control algorithm is proposed to satisfy the requirements of both user's data rate and signal quality. This algorithm lets only one representative user in each cell participate in the distributed power control and assigns the power levels to other users according to some constant power ratios. In addition to reducing the computational complexity, the proposed algorithm also gains larger throughput for the same number of iterations and finds a feasible power set faster than the other algorithm does.

The aggregation of Wi-Fi links has been identified as one way of taking advantage of available channels to achieve higher speed data transmission in future cognitive radio networks. However variations in link quality make it difficult to achieve stable performance from aggregated Wi-Fi links. In this paper we present a method for controlling aggregation of Wi-Fi links based on monitoring of link status. We first discuss the requirements for detecting bad-links which degrade the performance of aggregated Wi-Fi links. We then describe the implementation of an enhanced link-status detection algorithm based on monitoring of signal strength and number of retransmissions. In particular, we address the problems of monitoring and recovering links after they have been dropped from use, and adjusting decision thresholds to adapt to changing wireless conditions. Finally, we report the results of tests which demonstrate the effectiveness for attaining efficient aggregation of Wi-Fi links for high throughput under varying wireless conditions.

The redox (Reduction-Oxidation) flow battery is one of the most promising rechargeable batteries due to its ability to average loads and output of power sources. The transient characteristics are well known as the remarkable feature of the battery. Then it can also compensate for a sudden voltage drop. The dynamics are governed by the chemical reactions, fluid flow, and electrical circuit of its structure. This causes the difficulty of the analysis at transient state. This paper discusses the transient behavior of the redox flow battery based on chemical reactions. The concentration change of vanadium ions depends on the chemical reactions and the flow of electrolysis solution. The chemical reaction rate is restricted by the attached external electric circuit. In this paper, a model of the transient behavior is introduced. The validity of the derived model is examined based on experiments for a tested micro-redox flow battery system.

A dynamic routing and wavelength assignment (RWA) algorithm encompassing physical impairment due to Four-Wave Mixing (FWM) is proposed, assuming conventional On-Off-Keying (OOK) modulation format. The FWM effect is one of the most severe physical impairments to be considered for the future photonic networks since the accumulation of FWM crosstalk causes a fatal degradation in the wavelength-routed optical network performance. A novel cost function is introduced based upon an impairment-constraint-based routing (ICBR) approach, taking into account the network utilization resources and the physical impairment due to FWM crosstalk. Simulations results show that the proposed algorithm leads to a more realistic system performance compared to those of related approaches of dynamic RWA that fail to consider physical impairments into the routing scheme.

In this paper, efficient symbol timing synchronization algorithms for IEEE 802.11a/g wireless LAN systems in multipath channels are proposed. For improved accuracy, the algorithms utilize an effectively elongated training symbol together with nonlinear soft-limiting of the correlator output. The algorithms allow efficient utilization of the guard interval in multipath channels. Simulation results show that the proposed algorithms significantly outperform conventional algorithms.

The least-squares linear filtering and fixed-point smoothing problems of uncertainly observed signals are considered when the signal and the observation additive noise are correlated at any sampling time. Recursive algorithms, based on an innovation approach, are proposed without requiring the knowledge of the state-space model generating the signal, but only the autocovariance and crosscovariance functions of the signal and the observation white noise, as well as the probability that the signal exists in the observations.

This paper addresses the problem of view invariant action recognition using 2D trajectories of landmark points on human body. It is a challenging task since for a specific action category, the 2D observations of different instances might be extremely different due to varying viewpoint and changes in speed. By assuming that the execution of an action can be approximated by dynamic linear combination of a set of basis shapes, a novel view invariant human action recognition method is proposed based on non-rigid matrix factorization and Hidden Markov Models (HMMs). We show that the low dimensional weight coefficients of basis shapes by measurement matrix non-rigid factorization contain the key information for action recognition regardless of the viewpoint changing. Based on the extracted discriminative features, the HMMs is used for temporal dynamic modeling and robust action classification. The proposed method is tested using real life sequences and promising performance is achieved.

The ability to mentalize is essential for human socialization. Such ability is strongly related to communication. In this paper, I discuss the development of mentalizing and communication from the perspectives of a new idea, Developmental Cybernetics, and developmental cognitive neuroscience. Children only attributed intention to a robot when they saw it behaving as a human and displaying social signals such as eye gaze. The emergence of powerful new methods and tools, such as neuroimaging, now allows questions about mentalizing to resolved more directly than before.

An all-optical phase multiplexing scheme for phase-modulated signals is proposed and experimentally demonstrated using four-wave mixing (FWM) in a highly-nonlinear fiber (HNLF). Two 10-Gb/s π/2-shifted differential phase-shift keying (DPSK) wavelength-division multiplexing (WDM) signals are experimentally demonstrated to be converted and phase-multiplexed into a 20-Gb/s differential quadrature phase-shift keying (DQPSK) signal with non-return-to-zero (NRZ) and return-to-zero (RZ) formats, respectively. Experimental results show that, due to phase-modulation-depth doubling effect and phase multiplexing effect in the FWM process, a DQPSK signal is successfully generated through the proposed all-optical phase multiplexing with improved receiver sensitivity and spectral efficiency.

For wideband MIMO-OFDM systems, scheduling and link adaptation are key techniques to improve the throughput performance. However, in systems without reciprocity between the uplink and the downlink channels, these techniques require a high feedback overhead of the channel quality indication (CQI) information. In this paper, we propose a novel CQI feedback reduction method, which is based on the conventional compression techniques exploiting the discrete cosine transformation (DCT). The basic idea is to adaptively permute the CQI sequences of different MIMO streams according to one of the possible patterns before the DCT compression so that the amount of feedback bits is minimized. The possible patterns used are carefully designed according to our analysis of the two types of correlations (the inter-stream correlation and the inter-subband correlation) that exist in MIMO-OFDM transmission, as well as their impact on the compression efficiency. Simulation results verify that the proposed method can effectively reduce the CQI feedback overhead under varying channel conditions.

Scalar multiplication methods using the Frobenius maps are known for efficient methods to speed up (hyper)elliptic curve cryptosystems. However, those methods are not efficient for the cryptosystems constructed on fields of small extension degrees due to costs of the field operations. Iijima et al. showed that one can use certain automorphisms on the quadratic twists of elliptic curves for fast scalar multiplications without the drawback of the Frobenius maps. This paper shows an extension of the automorphisms on the Jacobians of hyperelliptic curves of arbitrary genus.

We formulated the excitation rate of VUV and emitted visible light from rare gas on PDP by using the Boltzmann equation with electron-atom collision integral term and obtained the excitation rate as the function of Temperature and Mass. This form of excitation rate was firstly derived in PDP area. In addition we showed the Pressure dependence of intensity ratio of Ne/VUV as the application of our excitation rate formulae.

In this paper, we present a robust small-object detection method, which we call "Frequency Pattern Emphasis Subtraction (FPES)", for wide-area surveillance such as that of harbors, rivers, and plant premises. For achieving robust detection under changes in environmental conditions, such as illuminance level, weather, and camera vibration, our method distinguishes target objects from background and noise based on the differences in frequency components between them. The evaluation results demonstrate that our method detected more than 95% of target objects in the images of large surveillance areas ranging from 30-75 meters at their center.