Salient edge detection which is mentioned less frequently than salient point detection is another important cue for subsequent processing in computer vision. How to find the salient edges in natural images is not an easy work. This paper proposes a simple method for salient edge detection which preserves the edges with more salient points on the boundaries and cancels the less salient ones or noise edges in natural images. According to the Gestalt Principles of past experience and entirety, we should not detect the whole edges in natural images. Only salient ones can be an advantageous tool for the following step just like object tracking, image segmentation or contour detection. Salient edges can also enhance the efficiency of computing and save the space of storage. The experiments show the promising results.

It is known that MIMO channel matrix condition number influences detectors performance. Several authors have proposed combined decoders, mainly suboptimal, to cope with this fact. These combined algorithms require an estimation of the MIMO channel matrix condition number and a selection of a suitable threshold condition number. This letter presents practical algorithms to carry out the referred tasks and shows their performance in practice.

A PN junction current model for advanced MOSFETs is proposed and implemented into HiSIM2, a complete surface-potential-based MOSFET model. The model includes forward diode currents and reverse diode currents, and requires a total of 13 model parameters covering all bias conditions. Model simulation results reproduce measurements for different device geometries over a wide range of bias and temperature values.

Tracking a large quantity of moving target tags simultaneously is essential for the localization and guidance of people in welfare facilities like hospitals and sanatoriums for the aged. The locating system using active RFID technology consists of a number of fixed RFID readers and tags carried by the target objects, or senior people. We compare the performances of several determination algorithms which use the power measurement of received signals emitted by the moving active RFID tags. This letter presents a study on the effect of collision in tracking large quantities of objects based on active RFID real time location system (RTLS). Traditional trilateration, fingerprinting, and well-known LANDMARC algorithm are evaluated and compared with varying number of moving tags through the SystemC-based computer simulation. From the simulation, we show the tradeoff relationship between the number of moving tags and estimation accuracy.

Various scanning algorithms have been proposed to enhance the performance of intra prediction of H.264 codec. In this paper, an adaptive scanning scheme is proposed to achieve the entropy coding gain in intra coding, where scanning patterns are updated based on the probabilistic distribution of quantized coefficients of previous macroblocks so that the consecutive zeros are located at the rear part of the scanned data stream. Simulation results show that the average bit-rate reduction is about 2.15% in common test conditions.

In this paper, a multi-cell joint channel estimation (JCE) method is proposed for the TD-SCDMA downlink. In the proposed multi-cell JCE approach, the received midambles from adjacent cells are jointly processed, rather than being treated as interference as in single cell channel estimation. By jointly processing all the received midambles, the user can simultaneously estimate the channel impulse responses (CIRs) for both its home cell and adjacent cells. If the received signal from adjacent cells has a delay, multi-cell JCE is still operable with slight adjustment in the midamble matrix, and the performance loss is also minor. The performance of multi-cell JCE is analyzed and evaluated by simulations. The results demonstrate that the proposed multi-cell JCE method can significantly improve the channel estimation accuracy. When the signal from each cell has similar power level, the mean square error (MSE) of the estimated CIRs for all cells is lower than 0.01. With more accurate CIRs from multi-cell JCE, multi-cell JD also yields better performance compared with the single cell channel estimation methods.

Salient Region Extraction provides an alternative methodology to image description in many applications such as adaptive content delivery and image retrieval. In this paper, we propose a robust approach to extracting the salient region based on bottom-up visual attention. The main contributions are twofold: 1) Instead of the feature parallel integration, the proposed saliencies are derived by serial processing between texture and color features. Hence, the proposed approach intrinsically provides an alternative methodology to model attention with low implementation complexity. 2) A constructive approach is proposed for rendering an image by a non-linear intensity mapping, which can efficiently eliminate high contrast noise regions in the image. And then the salient map can be robustly generated for a variety of nature images. Experiments show that the proposed algorithm is effective and can characterize the human perception well.

As we scale toward nanometer technologies, the increase in interconnect parameter variations will bring significant performance variability. New design methodologies will emerge to facilitate construction of reliable systems from unreliable nanometer scale components. Such methodologies require new performance models which accurately capture the manufacturing realities. In this paper, we present a Linear Fractional Transform (LFT) based model for interconnect parametric uncertainty. The new model formulates the interconnect parametric uncertainty as a repeated scalar uncertainty structure. With the help of generalized Balanced Truncation Realization (BTR) and Linear Matrix Inequalities (LMI's), the porposed model reduces the order of the original interconnect network while preserves the stability. The LFT based new model even guarantees passivity if the BTR reduction is based on solutions to a pair of Linear Matrix Inequalities (LMI's) generated from Lur'e equations. In case of large number of uncertain parameters, the new model may be applied successively: the uncertain parameters are partitioned into groups, and with regard to each group, LFT based model is applied in turns.

The ability of a modified bow-tie dipole antenna, which has an asymmetric-feed structure to operate at UHF-band (470-862 MHz) and dual ISM-band (2.4 GHz and 5.8 GHz) is demonstrated. Experimental results indicate that the VSWR 2:1 bandwidths achieved were 125.7%, 8.2% and 23.6% at 660 MHz, 2.45 GHz and 5.5 GHz. The proposed modified bow-tie dipole exhibits a nearly omni-directional radiation pattern with very easy to fabricate structure, and so is suitable for various commercial wideband applications.

In this article, we introduce a new concept for the future information environment, called an "ambient information environment (AmIE)." We first explain it, especially emphasizing the difference from the existing ubiquitous information environment (UbIE), which is an interaction between users and environments. Then, we focus on an ambient networking environment (AmNE) which supports the AmIE as a networking infrastructure. Our approach of a biologically inspired framework is next described in order to demonstrate why such an approach is necessary in the AmIE. Finally, we show some example for building the AmNE.

This paper presents a cache way enabling mechanism using branch target addresses. This mechanism uses branch prediction information to avoid the power consumption due to unnecessary cache way access by enabling only the cache way(s) that should be accessed. The proposed cache way enabling mechanism reduces the power consumption of the instruction cache by 63% without any performance degradation of the processor. An ARM1136 processor simulator and the Synopsys PrimeTime are used to perform the performance/power simulation and static timing analysis of the proposed mechanisms respectively.

For variation-aware capacitance extraction, stochastic collocation method (SCM) based on Homogeneous Chaos expansion has the exponential convergence rate for Gaussian geometric variations, and is considered as the optimal solution using a quadratic model to model the parasitic capacitances. However, when geometric variations are measured from the real test chip, they are not necessarily Gaussian, which will significantly compromise the exponential convergence property of SCM. In order to pursue the exponential convergence, in this paper, a generalized stochastic collocation method (gSCM) based on generalized Polynomial Chaos (gPC) expansion and generalized Sparse Grid quadrature is proposed for variation-aware capacitance extraction that further considers the arbitrary random probability of real geometric variations. Additionally, a recycling technique based on Minimum Spanning Tree (MST) structure is proposed to reduce the computation cost at each collocation point, for not only "recycling" the initial value, but also "recycling" the preconditioning matrix. The exponential convergence of the proposed gSCM is clearly shown in the numerical results for the geometric variations with arbitrary random probability.

Cooperative transmission is an efficient approach to improve the performance of wireless communications over fading channels without the need for physical co-located antenna arrays. In this paper, we propose a novel cooperative protocol with selective decode-and-forward relays and generalized selection combining (GSC) technique at destination. The advantage of this scheme is that it not only allows us to optimize the structure of destination but also to fully exploit the diversity offered by the channels with an appropriate number of chosen strongest paths. For an arbitrary number of relays, an exact and closed-form expression of the Symbol Error Rate (SER) is derived for M-ary PSK in independent but not identically distributed Rayleigh fading channels. Various simulations are performed and their results exactly match the results of analyses.

In this paper, a novel model of Gaussian pulse propagation in optical fiber is proposed to comprehensively analyze the impact of Group Velocity Dispersion (GVD) on the performance of two-dimensional wavelength hopping/time spreading optical code division multiple access (2-D WH/TS OCDMA) systems. In addition, many noise and interferences, including multiple access interference (MAI), optical beating interference (OBI), and receiver's noise are included in the analysis. Besides, we propose to use the heterodyne detection receiver so that the receiver's sensitivity can be improved. Analytical results show that, under the impact of GVD, the number of supportable users is extremely decreased and the maximum transmission length (i.e. the length at which BER 10-9 can be maintained) is remarkably shortened in the case of normal single mode fiber (ITU-T G.652) is used. The main factor that limits the system performance is time skewing. In addition, we show how the impact of GVD is relieved by dispersion-shifted fiber (ITU-T G.653). For example, a system with 321 Gbit/s users can achieve a maximum transmission length of 111 km when transmitted optical power per bit is -5 dBm.

The core of the support vector machine (SVM) problem is a quadratic programming problem with a linear constraint and bounded variables. This problem can be transformed into the second order cone programming (SOCP) problems. An interior-point-method (IPM) can be designed for the SOCP problems in terms of storage requirements as well as computational complexity if the kernel matrix has low-rank. If the kernel matrix is not a low-rank matrix, it can be approximated by a low-rank positive semi-definite matrix, which in turn will be fed into the optimizer. In this paper we present two SOCP formulations for each SVM classification and regression problem. There are several search direction methods for implementing SOCPs. Our main goal is to find a better search direction for implementing the SOCP formulations of the SVM problems. Two popular search direction methods: HKM and AHO are tested analytically for the SVM problems, and efficiently implemented. The computational costs of each iteration of the HKM and AHO search direction methods are shown to be the same for the SVM problems. Thus, the training time depends on the number of IPM iterations. Our experimental results show that the HKM method converges faster than the AHO method. We also compare our results with the method proposed in Fine and Scheinberg (2001) that also exploits the low-rank of the kernel matrix, the state-of-the-art SVM optimization softwares SVMTorch and SVMlight. The proposed methods are also compared with Joachims 'Linear SVM' method on linear kernel.

The proposed quasi-resonant (QR) zero current switching (ZCS) switched-capacitor (SC) converter is a new type of bidirectional power flow control conversion scheme. The proposed converter is able to provide voltage conversion ratios from -3/- (triple-mode/ trisection-mode) to -n/- (-n-mode/--mode) by adding a different number of switched-capacitors and power MOSFET switches with a small series connected resonant inductor for forward and reverse power flow control schemes. It possesses the advantages of low switching losses and current stress in this QR ZCS SC converter. The principle of operation, theoretical analysis of the proposed triple-mode/ trisection-mode bidirectional power conversion scheme is described in detail with circuit model analysis. Simulation and experimental studies are carried out to verify the performance of the proposed inverting type ZCS SC QR bidirectional converter. The proposed converters can be applied to battery equalization for battery management system (BMS).

This paper proposes an adaptive selection algorithm for the surviving symbol replica candidates (ASESS) based on the maximum reliability in maximum likelihood detection with QR decomposition and the M-algorithm (QRM-MLD) for Orthogonal Frequency Division Multiplexing (OFDM) multiple-input multiple-output (MIMO) multiplexing. In the proposed algorithm, symbol replica candidates newly-added at each stage are ranked for each surviving symbol replica from the previous stage using multiple quadrant detection. Then, branch metrics are calculated only for the minimum number of symbol replica candidates with a high level of reliability using an iterative loop based on symbol ranking results. Computer simulation results show that the computational complexity of the QRM-MLD employing the proposed ASESS algorithm is reduced to approximately 1/4 and 1/1200 compared to that of the original QRM-MLD and that of the conventional MLD with squared Euclidian distance calculations for all symbol replica candidates, respectively, assuming the identical achievable average packet error rate (PER) performance in 4-by-4 MIMO multiplexing with 16QAM data modulation. The results also show that 1-Gbps throughput is achieved at the average received signal energy per bit-to-noise power spectrum density ratio (Eb/N0) per receiver antenna of approximately 9 dB using the ASESS algorithm in QRM-MLD associated with 16QAM modulation and Turbo coding with the coding rate of 8/9 assuming a 100-MHz bandwidth for a 12-path Rayleigh fading channel (root mean square (r.m.s.) delay spread of 0.26 µs and maximum Doppler frequency of 20 Hz).

CMOS circuits consume great dynamic power in switching. It has been proposed that energy transfer through a rising Vdd dissipates small amounts of energy. In typical power gate circuits, the high-performance PMOS transistors (PSW) that connect the circuit blocks to the power supply reduce leakage power by shutting off outer power (Vdd) to the idle blocks. We expand this technique by utilizing active PSW, which are turned on and off by clock signal. The PSW are fully turned on only for half of each clock cycle. This means that sufficient Vdd is provided to the circuit continuously for half of each clock cycle. In this manner, the circuit charge and discharge actions are cycle occur in different phases, and ramp Vdd is supplied to the designed circuit; we name this technique "CKVdd." CKVdd is a clock-controlled self-stabilized voltage technique, which generates stable ramp voltage to suppress the currents effectively. It is proposed to reduce dynamic power dissipation in conventional CMOS digital circuits. As compared to the conventional circuit, the circuits using CKVdd technique possesses several characteristics that differ from those of the current circuits using constant Vdd power source. First, CKVdd technique combines the power source and clock signal; it is an efficient low power technique. Second, CKVdd propose a feasible method to generate ramp-Vdd and low-Vdd. This technique would be convenient used to design generic low power digital circuits. Third, normal CMOS circuits show the dynamic power consumption increase proportional to the clock frequency. CKVdd results in a lower-than-usual frequency dependency, it is suitable used to design high clock speed circuits. In investigating constant Vdd for MPEG VLD decoders, CKVdd-circuit reduces 48% of the usual power dissipation and 88% of the usual peak current with small delay penalty.

Topology information has become more important for management of LANs due to the increasing number of hosts attached to a LAN. We describe three Ethernet topology discovery techniques that can be used even in LANs with Ethernet switches that have no management functionality. Our "Shared Switch Detection (SSD)" technique detects the Ethernet tree topology by testing whether two paths in the network share a switch. SSD uses only general MAC address learning. By borrowing MAC addresses from hosts, SSD can be run from a single host. The second technique determines whether two paths between two pairs of hosts contain a switch. The third reduces the number of shared switch detections. Simulation showed that these techniques can be used to detect the Ethernet topology with a reasonable search cost. Examination on a real-world testbed showed that they could detect an Ethernet topology consisting of six hosts and two switches within one second.

This paper describes a distinctive phonetic feature (DPF) extraction method for use in a phoneme recognition system; our method has a low computation cost. This method comprises three stages. The first stage uses two multilayer neural networks (MLNs): MLNLF-DPF, which maps continuous acoustic features, or local features (LFs), onto discrete DPF features, and MLNDyn, which constrains the DPF context at the phoneme boundaries. The second stage incorporates inhibition/enhancement (In/En) functionalities to discriminate whether the DPF dynamic patterns of trajectories are convex or concave, where convex patterns are enhanced and concave patterns are inhibited. The third stage decorrelates the DPF vectors using the Gram-Schmidt orthogonalization procedure before feeding them into a hidden Markov model (HMM)-based classifier. In an experiment on Japanese Newspaper Article Sentences (JNAS) utterances, the proposed feature extractor, which incorporates two MLNs and an In/En network, was found to provide a higher phoneme correct rate with fewer mixture components in the HMMs.