We have succeeded in demonstrating high-performance four-channel 25 Gb/s integrated receiver for 100 Gb/s Ethernet with a built-in spatial Demux optics and an integrated PD array. All components which configure to the Demux optics adhered to a prism. Because of the shaping accuracy for prism, the insertion loss was able to suppress to 0.8 dB with small size. The connection point of the package for high speed electrical signals was improved to decrease the transmission loss. The small size of 12 mm 17 mm 7 mm compact package with a side-wall electrical connector has been achieved, which is compatible with the assembly in CFP2 form-factor. We observed the sensitivity at average power of -12.1 dBm and the power penalty of sensitivity due to the crosstalk of less than 0.1 dB.

The simple repetitive control system proposed by Yamada et al. is a type of servomechanism for periodic reference inputs. This system follows a periodic reference input with a small steady-state error, even if there is periodic disturbance or uncertainty in the plant. In addition, simple repetitive control systems ensure that transfer functions from the periodic reference input to the output and from the disturbance to the output have finite numbers of poles. Yamada et al. clarified the parameterization of all stabilizing simple repetitive controllers. Recently, Yamada et al. proposed the parameterization of all stabilizing two-degrees-of-freedom (TDOF) simple repetitive controllers that can specify the input-output characteristic and the disturbance attenuation characteristic separately. However, when using the method of Yamada et al., it is complex to specify the low-pass filter in the internal model for the periodic reference input that specifies the frequency characteristics. This paper extends the results of Yamada et al. and proposes the parameterization of all stabilizing TDOF simple repetitive controllers with specified frequency characteristics in which the low-pass filter can be specified beforehand.

This paper provides a novel normalized sign least-mean square (NSLMS) algorithm which updates only a part of the filter coefficients and simultaneously performs sparse updates with the goal of reducing computational complexity. A combination of the partial-update scheme and the set-membership framework is incorporated into the context of L∞-norm adaptive filtering, thus yielding computational efficiency. For the stabilized convergence, we formulate a robust update recursion by imposing an upper bound of a step size. Furthermore, we analyzed a mean-square stability of the proposed algorithm for white input signals. Experimental results show that the proposed low-complexity NSLMS algorithm has similar convergence performance with greatly reduced computational complexity compared to the partial-update NSLMS, and is comparable to the set-membership partial-update NLMS.

Online resource management of a software system can take advantage of a performance model to predict the effect of proposed changes. However, the prediction accuracy may degrade if the performance model does not adapt to the changes in the system. This work considers the problem of using Kalman filters to track changes in both performance model parameters and system behavior. We propose a method based on the multiple-model Kalman filter. The method runs a set of Kalman filters, each of which models different system behavior, and adaptively fuses the output of those filters for overall estimates. We conducted case studies to demonstrate how to use the method to track changes in various system behaviors: performance modeling, process modeling, and measurement noise. The experiments show that the method can detect changes in system behavior promptly and significantly improve the tracking and prediction accuracy over the single-model Kalman filter. The influence of model design parameters and mode-model mismatch is evaluated. The results support the usefulness of the multiple-model Kalman filter for tracking performance model parameters in systems with time-varying behavior.

Super resolution (SR) reconstruction is the process of fusing a sequence of low-resolution images into one high-resolution image. Many researchers have introduced various SR reconstruction methods. However, these traditional methods are limited in the extent to which they allow recovery of high-frequency information. Moreover, due to the self-similarity of face images, most of the facial SR algorithms are machine learning based. In this paper, we introduce a facial SR algorithm that combines learning-based and regularized SR image reconstruction algorithms. Our conception involves two main ideas. First, we employ separated frequency components to reconstruct high-resolution images. In addition, we separate the region of the training face image. These approaches can help to recover high-frequency information. In our experiments, we demonstrate the effectiveness of these ideas.

Rotate magnetic field can be used for ranging, especially the environment where electronic filed suffers a deep fading and attenuation, such as drilling underground. However, magnetic field is still affected by the ferromagnetic materials, e.g., oil casing pipe. The measurement error is not endurable for single measurement. In this paper, the Geometric Predicted Unscented Kalman Filtering (GP-UKF) algorithm is developed for rotate magnetic ranging system underground. With GP-UKF, the Root Mean Square Error (RMSE) can be suppressed. It is really important in a long range detection by magnetic field, i.e., more than 50 meters.

Adverse weather, such as rain or snow, can cause difficulties in the processing of video streams. Because the appearance of raindrops can affect the performance of human tracking and reduce the efficiency of video compression, the detection and removal of rain is a challenging problem in outdoor surveillance systems. In this paper, we propose a new algorithm for rain detection and removal based on both spatial and wavelet domain features. Our system involves fewer frames during detection and removal, and is robust to moving objects in the rain. Experimental results demonstrate that the proposed algorithm outperforms existing approaches in terms of subjective and objective quality.

As the successive video compression standard of H.264/AVC, High Efficiency Video Codec (HEVC) will play an important role in video coding area. In the deblocking filter part, HEVC inherits the basic property of H.264/AVC and gives some new features. Based on this variation, this paper introduces a novel dual-mode deblocking filter architecture which could support both of the HEVC and H.264/AVC standards. For HEVC standard, the proposed symmetric unified-cross unit (SUCU) based filtering scheme greatly reduces the design complexity. As a result, processing a 1616 block needs 24 clock cycles. For H.264/AVC standard, it takes 48 clock cycles for a 1616 macro-block (MB). In synthesis result, the proposed architecture occupies 41.6k equivalent gate count at frequency of 200 MHz in SMIC 65 nm library, which could satisfy the throughput requirement of super hi-vision (SHV) on 60 fps. With filter reusing scheme, the universal design for the two standards saves 30% gate counts than the dedicated ones in filter part. In addition, the total power consumption could be reduced by 57.2% with skipping mode when the edges need not be filtered.

In this paper, we propose a novel camera identification method based on photo-response non-uniformity (PRNU), which performs well even with rotated videos. One of the disadvantages of the PRNU-based camera identification methods is that they are very sensitive to de-synchronization. If a video under investigation is slightly rotated, the identification process without synchronization fails. The proposed method solves this kind of out-of-sync problem, by achieving rotation-tolerance using Optimal Tradeoff Circular Harmonic Function (OTCHF) correlation filter. The experimental results show that the proposed method identifies source device with high accuracy from rotated videos.

TransferJetTM is an emerging high-speed close-proximity wireless communication standard, which enables a data transfer up to 522 Mbps within a few centimeters range. We present a fully integrated TransferJet SoC with a 4.48-GHz operating frequency and a 560-MHz signal bandwidth using a 65 nm CMOS technology. Baseband filtering techniques for a transmitter (TX) and a receiver (RX) are proposed in order to handle the ultra-wide bandwidth with low power consumption and small area. A programmable power attenuator (PAT) for precise output power is also proposed in this paper. The SoC achieves energy efficiencies of 0.19 nJ/bit and 0.43 nJ/bit for the TX and the RX, respectively. The RX sensitivity of -70 dBm for 522 Mbps data rate and the TX error vector magnitude (EVM) of -31 dB are achieved.

The wideband noise controlling performance of the delayless subband adaptive filtering technique is affected by the group delay and in-band aliasing distortion of analysis filter banks. A method of recursive second-order cone programming is proposed to design the uniform DFT modulated analysis filter banks, with a small in-band aliasing error and low group delay. Simulation results show that the noise controlling performance is improved with small residual noise power spectra, a high noise attenuation level and fast convergence rate.

The noise in digital images acquired by image sensors has complex characteristics due to the variety of noise sources. However, most noise reduction methods assume that an image has additive white Gaussian noise (AWGN) with a constant standard deviation, and thus such methods are not effective for use with image signal processors (ISPs). To efficiently reduce the noise in an ISP, we estimate a unified noise model for an image sensor that can handle shot noise, dark-current noise, and fixed-pattern noise (FPN) together, and then we adaptively reduce the image noise using an adaptive Smallest Univalue Segment Assimilating Nucleus ( SUSAN ) filter based on the unified noise model. Since our noise model is affected only by image sensor gain, the parameters for our noise model do not need to be re-configured depending on the contents of image. Therefore, the proposed noise model is suitable for use in an ISP. Our experimental results indicate that the proposed method reduces image sensor noise efficiently.

We present a small-area second-order all-digital time-to-digital converter (TDC) with two frequency shift oscillators (FSOs) comprising inverter chains and dynamic flipflops featuring low jitter. The proposed FSOs can maintain their phase states through continuous oscillation, unlike conventional gated ring oscillators (GROs) that are affected by transistor leakage. Our proposed FSOTDC is more robust and is eligible for all-digital TDC architectures in recent leaky processes. Low-jitter dynamic flipflops are adopted as a quantization noise propagator (QNP). A frequency mismatch occurring between the two FSOs can be canceled out using a least mean squares (LMS) filter so that second-order noise shaping is possible. In a standard 65-nm CMOS process, an SNDR of 61 dB is achievable at an input bandwidth of 500 kHz and a sampling rate of 16 MHz, where the respective area and power are 700 µm2 and 281 µW.

This paper presents a fully differential third-order (2-1) switched-current (SI) cascaded delta-sigma modulator (DSM), with an analog error cancellation logic circuit, and a digital decimation filter that is fabricated using 0.18-µm CMOS technology. The 2-1 architecture with only the quantizer input being fed into the second stage is introduced not only to reduce the circuit complexity, but also to be implemented easily using the switched-current approach. Measurements reveal that the dominant error is the quantization error of the second one-bit quantizer (e2). This error can be eliminated using an analog error cancellation logic circuit. In the proposed differential sample-and-hold circuit, low input impedance is presented with feedback and width-length adjustment in SI feedback memory cell (FMC); and that a coupled differential replicate (CDR) common-mode feedforward circuit (CMFF) is used to compensate the error of the current mirror. Also, measurements indicate that the signal-to-noise ratio (SNR), dynamic range (DR), effective number of bits (ENOB), power consumption and chip size are 67.3 dB, 69 dB, 10.9 bits, 12.3 mW, and 0.200.21 mm2, respectively, with a bandwidth of 40 kHz, a sampling rate of 10.24 MHz, an OSR of 128 and a supply voltage of 1.8 V.

This letter proposes an analog active noise control (ANC) circuit with an all-pass filter (APF). To improve performance of the previously reported analog ANC circuit, we inserted an APF to the circuit in order to fit phases of a noise and an electrical signal in the circuit. As a result, we confirmed improvement of the noise canceling effect of the analog ANC circuit.

This paper proposes a new adaptive comb filter which automatically designs its characteristics. The comb filter is used to eliminate a periodic noise from an observed signal. To design the comb filter, there exists three important factors which are so-called notch frequency, notch gain, and notch bandwidth. The notch frequency is the null frequency which is aligned at equally spaced frequencies. The notch gain controls an elimination quantity of the observed signal at notch frequencies. The notch bandwidth controls an elimination bandwidth of the observed signal at notch frequencies. We have previously proposed a comb filter which can adjust the notch gain adaptively to eliminate the periodic noise. In this paper, to eliminate the periodic noise when its frequencies fluctuate, we propose the comb filter which achieves the adaptive notch gain and the adaptive notch bandwidth, simultaneously. Simulation results show the effectiveness of the proposed adaptive comb filter.

During the production of speech signals, the vowel onset point is an important event containing important information for many speech processing tasks, such as consonant-vowel unit recognition and speech end-points detection. In order to realize accurate automatic detection of vowel onset points, this paper proposes a reliable method using the energy characteristics of homomorphic filtered spectral peaks. The homomorphic filtering helps to separate the slowly varying vocal tract system characteristics from the rapidly fluctuating excitation characteristics in the cepstral domain. The distinct vocal tract shape related to vowels is obtained and the peaks in the estimated vocal tract spectrum provide accurate and stable information for VOP detection. Performance of the proposed method is compared with the existing method which uses the combination of evidence from the excitation source, spectral peaks, and modulation spectrum energies. The detection rate with different time resolutions, together with the missing rate and spurious rate, are used for comprehensive evaluation of the performance on continuous speech taken from the TIMIT database. The detection accuracy of the proposed method is 74.14% for ±10 ms resolution and it increases to 96.33% for ±40 ms resolution with 3.67% missing error and 4.14% spurious error, much better than the results obtained by the combined approach at each specified time resolution, especially the higher resolutions of ±10±30 ms. In the cases of speech corrupted by white noise, pink noise and f-16 noise, the proposed method also shows significant improvement in the performance compared with the existing method.

In precoded TDD MIMO systems, precoding is done based on the downlink CSI, which can be predicted according to the outdated uplink CSI. This letter proposes a double-scale channel prediction scheme where frame-scale Kalman filters and pilot-symbol-scale AR predictors jointly predict the needed downlink CSI.

Estimating a proper location of vanishing point from a single road image without any prior known camera parameters is a challenging problem due to limited information from the input image. Most edge-based methods for vanishing point detection only work well for structured roads with clear painted lines or distinct boundaries, while they usually fail in unstructured roads lacking sharply defined, smoothly curving edges. In order to overcome this limitation, texture-based methods for vanishing point detection have been widely published. Authors of these methods often calculate the texture orientation at every pixel of the road image by using directional filter banks such as Gabor wavelet filter, and seek the vanishing point by a voting scheme. A local adaptive soft voting method for obtaining the vanishing point was proposed in a previous study. Although this method is more effective and faster than prior texture-based methods, the associated computational cost is still high due to a large number of scanning pixels. On the other hand, this method leads to an estimation error in some images, in which the radius of the proposed half-disk voting region is not large enough. The goal of this paper is to reduce the computational cost and improve the performance of the algorithm. Therefore, we propose a novel local soft voting method, in which the number of scanning pixels is much reduced, and a new vanishing point candidate region is introduced to improve the estimation accuracy. The proposed method has been implemented and tested on 1000 road images which contain large variations in color, texture, lighting condition and surrounding environment. The experimental results demonstrate that this new voting method is both efficient and effective in detecting the vanishing point from a single road image and requires much less computational cost when compared to the previous voting method.

Process variation causes significant fluctuations in the timing performance of analog circuits, which causes a fraction of circuits to fail specifications. By testing the delay-performance, we can recognize the failed circuits during production testing. In this paper, we have proposed a low overhead and process tolerant delay evaluation circuit for built-in self test (BIST) function for analog differential circuits. This circuit contains a delay generation cell, an input differential signal generation cell, a delay matching cell, a sample-hold circuit, and a comparator. This circuit was implemented with 0.18 µm CMOS process. Simulation results over process variation, devices mismatch and layout parasitics, but without silicon measurement, show that the accuracy in delay detection is within 5 ps. A case study was done over a feed-forward equalizer (FFE). A typical use of this circuit is testing the delay of various FIR (Finite Impulse Response) filters.