We achieved first dynamic all-optical signal processing with a bandgap-engineered MZI SOA all-optical switch. The wide-gap Selective Area Growth (SAG) technique was used to provide multi-bandgap materials with a single step epitaxy. The maximum photoluminescence (PL) peak shift obtained between the active region and the passive region was 192 nm. The static current switching with the fabricated switch indicated a large carrier induced refractive index change; up to 14 π phase shift was obtained with 60 mA injection in the SOA. The carrier recovery time of the SOA for obtaining a phase shift of π was estimated to be 250-300 ps. A clear eye pattern was obtained in 2.5 Gbps all-optical wavelength conversion. This is the first all-optical wavelength conversion demonstration with a bandgap-engineered PIC with either selective area growth or quantum-well intermixing techniques.

This paper deals with a secret key agreement problem from correlated random numbers. It is proved that there is a pair of linear matrices that yields a secret key agreement in the situation wherein a sender, a legitimate receiver, and an eavesdropper have access to correlated random numbers. A relation between the coding problem of correlated sources and a secret key agreement problem from correlated random numbers are also discussed.

In this paper, we proposed a new Two-Dimensional Linear Discriminant Analysis (2DLDA) method, based on Two-Dimensional Principle Component Analysis (2DPCA) concept. In particular, 2D face image matrices do not need to be previously transformed into a vector. In this way, the spatial information can be preserved. Moreover, the 2DLDA also allows avoiding the Small Sample Size (SSS) problem, thus overcoming the traditional LDA. We combine 2DPCA and our proposed 2DLDA on the Two-Dimensional Linear Discriminant Analysis of principle component vectors framework. Our framework consists of two steps: first we project an input face image into the family of projected vectors via 2DPCA-based technique, second we project from these space into the classification space via 2DLDA-based technique. This does not only allows further reducing of the dimension of feature matrix but also improving the classification accuracy. Experimental results on ORL and Yale face database showed an improvement of 2DPCA-based technique over the conventional PCA technique.

Developing embedded parallel image processing applications is usually a very hardware-dependent process, often using the single instruction multiple data (SIMD) paradigm, and requiring deep knowledge of the processors used. Furthermore, the application is tailored to a specific hardware platform, and if the chosen hardware does not meet the requirements, it must be rewritten for a new platform. We have proposed the use of design space exploration [9] to find the most suitable hardware platform for a certain application. This requires a hardware-independent program, and we use algorithmic skeletons [5] to achieve this, while exploiting the data parallelism inherent to low-level image processing. However, since different operations run best on different kinds of processors, we need to exploit task parallelism as well. This paper describes how we exploit task parallelism using an asynchronous remote procedure call (RPC) system, optimized for low-memory and sparsely connected systems such as smart cameras. It uses a futures [16]-like model to present a normal imperative C-interface to the user in which the skeleton calls are implicitly parallelized and pipelined. Simulation provides the task dependency graph and performance numbers for the mapping, which can be done at run time to facilitate data dependent branching. The result is an easy to program, platform independent framework which shields the user from the parallel implementation and mapping of his application, while efficiently utilizing on-chip memory and interconnect bandwidth.

In this study, we propose an adaptive handoff scheme with dynamic hysteresis value for cellular communications, which is based on distance between the mobile station and the serving base station. Performance is evaluated in terms of the expected number of handoffs, the expected handoff delay, standard deviation of handoff location, and the expected link degradation probability as well. Numerical results and simulations show that the proposed scheme outperforms the handoff schemes with static hysteresis levels. The effect of distance error is also discussed.

A second-order CMOS continuous-time bandpass filter with a tuneable 4-12 MHz center frequency (fc) is presented. The Design has been done by using a new second-order block which is based on Gm-C method. This Gm-C filter achieves a dynamic range of 30 dB for 1% IM3, and Q equal to 58 at 12 MHz, while dissipating only 10.5 mW from 3.3 V power supply in 0.35 µm CMOS process. The on-chip indirect automatic tuning circuit uses a phase-locked loop which sets filter center frequency to an external reference clock.

In this paper, we present a method for recognition of human activity as a series of actions from an image sequence. The difficulty with the problem is that there is a chicken-egg dilemma that each action needs to be extracted in advance for its recognition but the precise extraction is only possible after the action is correctly identified. In order to solve this dilemma, we use as many models as actions of our interest, and test each model against a given sequence to find a matched model for each action occurring in the sequence. For each action, a model is designed so as to represent any activity containing the action. The hierarchical hidden Markov model (HHMM) is employed to represent the models, in which each model is composed of a submodel of the target action and submodels which can represent any action, and they are connected appropriately. Several experimental results are shown.

Localization of a vehicle is a key component for driving assistance or autonomous navigation. In this work, we propose a visual positioning system (VPS) for vehicle or mobile robot navigation. Different from general landmark-based or model-based approaches, which rely on some predefined known landmarks or a priori information about the environment, no assumptions on the prior knowledge of the scene are made. A stereo-based vision system is built for both extracting feature correspondences and recovering 3-D information of the scene from image sequences. Relative positions of the camera motion are then estimated by registering the 3-D feature points from two consecutive image frames. Localization of the mobile platform is finally given by the reference to its initial position.

In this paper, we propose a new method that can remove view-disturbing noises from stereo images. One of the thorny problems in outdoor surveillance by a camera is that adherent noises such as waterdrops on the protecting glass surface lens disturb the view from the camera. Therefore, we propose a method for removing adherent noises from stereo images taken with a stereo camera system. Our method is based on the stereo measurement and utilizes disparities between stereo image pair. Positions of noises in images can be detected by comparing disparities measured from stereo images with the distance between the stereo camera system and the glass surface. True disparities of image regions hidden by noises can be estimated from the property that disparities are generally similar with those around noises. Finally, we can remove noises from images by replacing the above regions with textures of corresponding image regions obtained by the disparity referring. Experimental results show the effectiveness of the proposed method.

The electroencephalogram (EEG) has become a widely used tool for investigating brain function. Brain signal source localization is a process of inverse calculation from sensor information (electric potentials for EEG) to the identification of multiple brain sources to obtain the locations and orientation parameters. In this paper, we describe a combination of the backpropagation neural network (BPNN) with the nonlinear least-square (NLS) method to localize two dipoles with reasonable accuracy and speed from EEG data computerized by two dipoles randomly positioned in the brain. The trained BPNN, obtains the initial values for the two dipoles through fast calculation and also avoids the influence of noise. Then the NLS method (Powell algorithm) is used to accurately estimate the two dipole parameters. In this study, we also obtain the minimum distance between the assumed dipole pair, 0.8 cm, in order to localize two sources from a smaller limited distance between the dipole pair. The present simulation results demonstrate that the combined method can allow us to localize two dipoles with high speed and accuracy, that is, in 20 seconds and with the position error of around 6.5%, and to reduce the influence of noise.

Point pattern matching (PPM) arises in areas such as pattern recognition, digital video processing and computer vision. In this study, a novel Genetic Algorithm (GA) based method for matching affine-related point sets is described. Most common techniques for solving the PPM problem, consist in determining the correspondence between points localized spatially within two sets and then find the proper transformation parameters, using a set of equations. In this paper, we use this fact that the correspondence and transformation matrices are two unitary polar factors of Grammian matrices. We estimate one of these factors by the GA's population and then evaluate this estimation by computing an error function using another factor. This approach is an easily implemented one and because of using the GA in it, its computational complexity is lower than other known methods. Simulation results on synthetic and real point patterns with varying amount of noise, confirm that the algorithm is very effective.

The RC mismatch among S/H stages for time-interleaved ADCs causes a phase error and a gain error and the phase error is dominant. The paper points out that clock skew and the phase error caused by the RC mismatch have similar effects on the sampling error and then can be compensated with the clock skew compensation. Simulation results agree well with the theoretical analysis. With the phase error compensation of RC mismatch, the SNDR in 14b ADC can be improved by more than 15 dB in the case that the bandwidth of S/H circuits is 3 times the sampling frequency. This paper also proposes a method of clock skew and RC mismatch compensation in time-interleaved sample-and-hold (S/H) circuits by sampling clock phase adjusting.

We observe the inter-carrier interference (ICI) caused by channel variation of the fading in time domain in orthogonal frequency division multiplexing (OFDM) systems. This observation allows us to propose simple two-stage equalizer to minimize the ICI. Simulation results show that the bit error rate (BER) performance of the proposed equalizer with much reduced complexity is comparable with that of the classical frequency domain linear minimum mean squared error (MMSE) equalizer.

A new method to reduce power consumption of a linear transconductor is proposed in this paper. The minimum tail current for the operation of the transconductor is supplied by a new current source circuit. The proposed circuit is based on a dynamic biasing current technique. Results of SPICE simulation show that the proposed technique is very effective to reduce power consumption of the transconductor.

A great deal of research has been made to model the vagueness and uncertainty in information retrieval. One such research is fuzzy ranking models, which have been showing their superior performance in handling the uncertainty involved in the retrieval process. However, these conventional fuzzy ranking models have a limited ability to incorporate the user preference when calculating the rank of documents. To address this issue, in this study we develop a new fuzzy ranking model based on the user preference. Through the experiments on the TREC-2 collection of Wall Street Journal documents, we show that the proposed method outperforms the conventional fuzzy ranking models.

In this paper, for the fully-implantable middle ear hearing devices (F-IMEHD), a transcutaneous recharging system that has the function of the bi-directional signal transmission with the implant module in a body as well as recharging battery has been designed and implemented. The electromagnetic coupling method using two coils has been adopted for the transfer of electrical power to recharge internal battery of the implant module. To increase the efficiency of power transfer, the switching frequency of recharging system is determined by the consideration of the resonance of LC tank circuits. The bidirectional signal transmission between the recharging system and the implant module has been designed through the on-off keying modulation of switching signal in the recharging system and the impedance variation of LC tank circuit in the implant module. Through the demonstration of the implemented system, it has been verified that the proposed system has the performance of bidirectional signal transmission with the implant module of F-IMEHDs as well as the battery recharging.

The explosive growth of wireless network users and the existence of various wireless services have demanded high throughput as well as user's quality-of-service (QoS) guarantees. In accordance with, this paper proposes a novel resource allocation scheme improving both the capability of QoS-provisioning for multiple users and the overall data throughput. Towards this, the modified resource allocation technique combined with the modified largest weighted delay first (M-LWDF) scheme will be exploited upon considering statistical channel behavior as well as real time queuing analysis connected to resource allocation. In order to verify the validity of the proposed resource allocation scheme, the time division multiple access (TDMA) system will be considered as a target application. The simulation results confirm that the proposed scheme gives rise to superior performance in a way of showing results of several performance measures under time-varying wireless fading channel.

This paper proposes a novel UWB ranging scheme employing 1-bit ADCs and analog window bank for energy collection. For an appropriate 1-bit ADC process DC offset is exploited and removed via performing analog low pass filter. To improve ranging accuracy in presence of ambiguity, dual overlapped window banks designated as primary and auxiliary windows are utilized. Corresponding to the proposed ranging scheme, its performance is verified by conducting simulations in two types of channel conditions. The simulation results show that the proposed ranging scheme performs well even in condensed multipath environment and low SNR situation.

The fast handover protocol adopted in a IPv6 hierarchical structure provides a seamless handover in wireless IP networks by minimizing the handover latency. To reduce the handover latency, the fast handover uses anticipation based on layer 2 trigger. Nonetheless, a mobile node can still lose its connection with the old link during the fast handover procedures. Accordingly, this paper analyzes the handover latency and packet delivery costs associated with fast handover failure cases based on a timing diagram.

This paper describes the design of a small-offset 12-bit CMOS charge-redistribution DAC using a weighted-mean flip-around sample-and-hold circuit (S/H). Flip-around S/H topology can realize small-offset characteristics, and it is effective to reduce power dissipation and chip area because independent feedback capacitors are not necessary. In this DAC the small-offset characteristic remains not only in amplification phase but also in sampling phase with the circuit technique. The design of 1.8 V, 50 MS/s fully differential DAC with output swing of 2 Vp-p has very small offset of 100 µV for the reset switch mismatch of 2%. A technique to improve dynamic performance measured by SFDR using damping resistors and switches at the output stage is also presented. The designed 12-bit DAC with 0.25 µm CMOS technology has low-power dissipation of 35 mW at 50 MS/s.