This letter presents an efficient method for the maritime Loran-C additional secondary factor (ASF) correction based on equivalent ground conductivity inversion. Using the proposed method, the accuracy of Loran-C system on maritime positioning, navigation, and timing (PNT) can be improved significantly with a limited number of surveys. Comparison with measured ASF results shows a root-mean-square error (RMSE) of less than 100 ns in most areas.

The non-reference method is widely useful to estimation picture quality on the decoder side. In this paper, we discuss the estimation method for spatial blur that divides the frequency zones by the absolute value of 64 coefficients with an 8-by-8 DCT and compares them. It is recognized that absolute blur estimation is possible with the decoded picture only.

The objective of pool-based incremental active learning is to choose a sample to label from a pool of unlabeled samples in an incremental manner so that the generalization error is minimized. In this scenario, the generalization error often hits a minimum in the middle of the incremental active learning procedure and then it starts to increase. In this paper, we address the problem of early labeling stopping in probabilistic classification for minimizing the generalization error and the labeling cost. Among several possible strategies, we propose to stop labeling when the empirical class-posterior approximation error is maximized. Experiments on benchmark datasets demonstrate the usefulness of the proposed strategy.

The performance of English automatic speech recognition systems decreases when recognizing spontaneous speech mainly due to multiple pronunciation variants in the utterances. Previous approaches address this problem by modeling the alteration of the pronunciation on a phoneme to phoneme level. However, the phonetic transformation effects induced by the pronunciation of the whole sentence have not yet been considered. In this article, the sequence-based pronunciation variation is modeled using a noisy channel approach where the spontaneous phoneme sequence is considered as a “noisy” string and the goal is to recover the “clean” string of the word sequence. Hereby, the whole word sequence and its effect on the alternation of the phonemes will be taken into consideration. Moreover, the system not only learns the phoneme transformation but also the mapping from the phoneme to the word directly. In this study, first the phonemes will be recognized with the present recognition system and afterwards the pronunciation variation model based on the noisy channel approach will map from the phoneme to the word level. Two well-known natural language processing approaches are adopted and derived from the noisy channel model theory: Joint-sequence models and statistical machine translation. Both of them are applied and various experiments are conducted using microphone and telephone of spontaneous speech.

A generalized version of sequential logic circuit based neuron models is presented, where the dynamics of the model is modeled by an asynchronous cellular automaton. Thanks to the generalizations in this paper, the model can exhibit various neuron-like waveforms of the membrane potential in response to excitatory and inhibitory stimulus. Also, the model can reproduce four groups of biological and model neurons, which are classified based on existence of bistability and subthreshold oscillations, as well as their underlying bifurcations mechanisms.

A low power and high performance with third order delta-sigma modulator for audio applications, fabricated in a 0.18 µm CMOS process, is presented. The modulator utilizes a third order noise shaping with only one opamp by using an opamp sharing technique. The opamp sharing among three integrator stages is achieved through the optimal operation timing, which makes use of the load capacitance differences between the three integrator stages. The designed modulator achieves 101.1 dB signal-to-noise ratio (A-weighted) and 101.5 dB dynamic range (A-weighted) with 7.5 mW power consumption from a 3.3 V supply. The die area is 1.27 mm2. The fabricated delta-sigma modulator achieves the highest figure-of-merit among published high performance low power audio delta-sigma modulators.

Reduction of the intensity noise in semiconductor lasers is an important subject for the higher performance of an application. Simultaneous usage of the superposition of high frequency current and the electric negative feedback loop was proposed to suppress the noise for the higher power operation of semiconductor lasers. Effective noise reduction of more than 25 dB with 80 mW operation was experimentally demonstrated.

Our research is focused on examining the video quality assessment model based on the MPEG-7 descriptor. Video quality is estimated by using several features based on the predicted frame quality such as average value, worst value, best value, standard deviation, and the predicted frame rate obtained from descriptor information. As a result, assessment of video quality can be conducted with a high prediction accuracy with correlation coefficient=0.94, standard deviation of error=0.24, maximum error=0.68 and outlier ratio=0.23.

This paper proposes a comb filter design method which utilizes two linear phase FIR filters for flexibly adjusting the comb filter's frequency response. The first FIR filter is used to individually adjust the notch gains, which denote the local minimum gains of the comb filter's frequency response. The second FIR filter is used to design the elimination bandwidths for individual notch gains. We also derive an efficient comb filter by incorporating these two FIR filters with an all-pass filter which is used in a conventional comb filter to accurately align the nulls with the undesired harmonic frequencies. Several design examples of the derived comb filter show the effectiveness of the proposed comb filter design method.

This paper presents a no-reference (NR) based video-quality estimation method for compressed videos which apply inter-frame prediction. The proposed method does not need bitstream information. Only pixel information of decoded videos is used for the video-quality estimation. An activity value which indicates a variance of luminance values is calculated for every given-size pixel block. The activity difference between an intra-coded frame and its adjacent frame is calculated and is employed for the video-quality estimation. In addition, a blockiness level and a blur level are also estimated at every frame by analyzing pixel information only. The estimated blockiness level and blur level are also taken into account to improve quality-estimation accuracy in the proposed method. Experimental results show that the proposed method achieves accurate video-quality estimation without the original video which does not include any artifacts by the video compression. The correlation coefficient between subjective video quality and estimated quality is 0.925. The proposed method is suitable for automatic video-quality checks when service providers cannot access the original videos.

We propose a primary traffic based multihop relaying algorithm with cooperative transmission (PTBMR-CT). It enlarges the hop transmission distances to reduce the number of cognitive relays on the route from the cognitive source (CS) to the cognitive destination (CD). In each hop, from the cognitive nodes in a specified area depending on whether the primary source (PS) transmits data to the primary destination (PD), the cognitive node that is farthest away from the cognitive relay that sends data is selected as the other one that receives data. However, when the PS is transmitting data to the PD, from the cognitive nodes in a specified area, another cognitive node is also selected and prepared to be the cognitive relay that receives data of cooperative transmission. Cooperative transmission is performed if the PS is still transmitting data to the PD when the cognitive relay that receives data of the next hop transmission is being searched. Simulation results show that the average number of cognitive relays is reduced by PTBMR-CT compared to conventional primary traffic based farthest neighbor relaying (PTBFNR), and PTBMR-CT outperforms conventional PTBFNR in terms of the average end-to-end reliability, the average end-to-end throughput, the average required transmission power of transmitting data from the CS to the CD, and the average end-to-end transmission latency.

This letter presents the architecture of multi-gigabit parallel demodulator suitable for demodulating high order QAM modulated signal and easy to implement on FPGA platform. The parallel architecture is based on frequency domain implementation of matched filter and timing phase correction. Parallel FIFO based delete-keep algorithm is proposed for timing synchronization, while a kind of reduced constellation phase-frequency detector based parallel decision feedback PLL is designed for carrier synchronization. A fully pipelined parallel adaptive blind equalization algorithm is also proposed. Their parallel implementation structures suitable for FPGA platform are investigated. Besides, in the demonstration of 2 Gbps demodulator for 16QAM modulation, the architecture is implemented and validated on a Xilinx V6 FPGA platform with performance loss less than 2 dB.

In this letter, a post-detection signal to noise ratio (SNR) is considered for transmit antenna selection, when a sorted QR decomposition (SQRD) algorithm is used for signal detection in spatial multiplexing (SM) ultra-wideband (UWB) multiple input multiple output systems. The post-detection SNR expression is obtained using a QR factorization algorithm based on a sorted Gram-Schmidt process. The employed antenna selection criterion is to utilize the largest minimum post-detection SNR value. It is shown via simulations that the antenna selection significantly enhances the BER performance of the SQRD-based SM UWB systems on a log-normal multipath fading channel.

Digital still cameras emerged following the introduction of the Sony Mavica analog prototype camera in 1981. These early cameras produced poor image quality and did not challenge film cameras for overall quality. By 1995 digital still cameras in expensive SLR formats had 6 mega-pixels and produced high quality images (with significant image processing). In 2005 significant improvement in image quality was apparent and lower prices for digital still cameras (DSCs) started a rapid decline in film usage and film camera sells. By 2010 film usage was mostly limited to professionals and the motion picture industry. The rise of DSCs was marked by a “pixel war” where the driving feature of the cameras was the pixel count where even moderate cost, ∼ $120, DSCs would have 14 mega-pixels. The improvement of CMOS technology pushed this trend of lower prices and higher pixel counts. Only the single lens reflex cameras had large sensors and large pixels. The drive for smaller pixels hurt the quality aspects of the final image (sharpness, noise, speed, and exposure latitude). Only today are camera manufactures starting to reverse their course and producing DSCs with larger sensors and pixels. This paper will explore why larger pixels and sensors are key to the future of DSCs.

In this paper, we propose a novel method of measuring the perceived picture quality of H.264 coded video based on parametric analysis of the coded bitstream. The parametric analysis means that the proposed method utilizes only bitstream parameters to evaluate video quality, while it does not have any access to the baseband signal (pixel level information) of the decoded video. The proposed method extracts quantiser-scale, macro block type and transform coefficients from each macroblock. These parameters are used to calculate spatiotemporal image features to reflect the perception of coding artifacts which have a strong relation to the subjective quality. A computer simulation shows that the proposed method can estimate the subjective quality at a correlation coefficient of 0.923 whereas the PSNR metric, which is referred to as a benchmark, correlates the subjective quality at a correlation coefficient of 0.793.

Our research is focused on examining a stereoscopic quality assessment model for stereoscopic images with disparate quality in left and right images for glasses-free stereo vision. In this paper, we examine the objective assessment model of 3-D images, considering the difference in image quality between each view-point generated by the disparity-compensated coding. A overall stereoscopic image quality can be estimated by using only predicted values of left and right 2-D image qualities based on the MPEG-7 descriptor information without using any disparity information. As a result, the stereoscopic still image quality is assessed with high prediction accuracy with correlation coefficient=0.98 and average error=0.17.

In this paper, we propose low complexity channel parameter tracking methods for adaptive OFDM MMSE channel estimation. Even though the MMSE estimation is one of the most accurate channel estimation methods, it requires several channel information including Doppler frequency, RMS (root mean squared) delay spread, and SNR. To implement the MMSE estimation, tracking of such parameters should be preceded. We propose methods to track the above 3 channel parameters. As for Doppler frequency estimation, we propose an extremum method with a parabolic model, which is a key contribution of this paper. We also analyze the computational complexity of the proposed algorithms. Simulations show that the proposed tracking algorithm tracks the parameters well, and performs better than the conventional fixed-parameter algorithm in terms of BER performance. The BER performance of the adaptive MMSE estimation is better than that of a fixed-parameter (robust) MMSE estimator by about 5 dB.

To reduce the cost of fault management in all-optical networks, it is a promising approach to detect the degradation of optical signal quality solely at the terminal points of all-optical monitoring paths. The all-optical monitoring paths must be routed so that all single-link failures can be localized using route information of monitoring paths where signal quality degradation is detected. However, route computation for the all-optical monitoring paths that satisfy the above condition is time consuming. This paper proposes a procedure for deriving the lower bounds of the required number of monitoring paths to localize all single-link failures, and proposes an efficient monitoring path computation method based on the derived lower bounds. The proposed method repeats the route computation for the monitoring paths until feasible routes can be found, while the assumed number of monitoring paths increases, starting from the lower bounds. With the proposed method, the minimum number of monitoring paths with the overall shortest routes can be obtained quickly by solving several small-scale integer linear programming problems when the possible terminal nodes of monitoring paths are arbitrarily given. Thus, the proposed method can minimize the required number of monitors for detecting the degradation of signal quality and the total overhead traffic volume transferred through the monitoring paths.

We propose a methodology of loop design optimization for fourth-order fractional-N phase locked loop (PLL) frequency synthesizers featuring a short settling time of 5 µsec for applications in an active RFID (radio frequency identification) and automobile smart-key systems. To establish the optimized design flow, equations presenting the relationship between the specification and PLL loop parameters in terms of settling time, loop bandwidth, phase margin, and phase noise are summarized. The proposed design flow overcomes the settling time inaccuracy in conventional second-order approximation methods by obtaining the accurate relationship between settling time and loop bandwidth with the MATLAB Control System Toolbox for the fourth-order PLLs. The proposed flow also features the worst-case design by taking account of the process, voltage, and temperature (PVT) variations in loop filter components, and considers the tradeoff between phase noise and area. The three-step optimization process consists of 1) the derivation of the accurate relationship between the settling time and loop bandwidth for various PVT conditions, 2) the derivation of phase noise and area as functions of area-dominant filter capacitance, and 3) the derivation of all PLL loop components values. The optimized design result is compared with circuit simulations using an actually designed fourth-order fractional-N PLL in a 1.8 V 0.18 µm CMOS technology. The error between the design and simulation for the setting time is reduced from 0.63 µsec in the second-order approximation to 0.23 µsec in the fourth-order optimization that proves the validity of the proposed method for the high-speed settling operations.

An asymmetric classifier based on kernel partial least squares is proposed for software defect prediction. This method improves the prediction performance on imbalanced data sets. The experimental results validate its effectiveness.