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.

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 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.

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.

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.

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.

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.

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 new technique to smooth speech feature vectors for text-independent speaker verification using an adaptive band-pass IIR filer. The filter is designed by considering the probability density of modulation-frequency components of an M-dimensional feature vector. Each dimension of the feature vector is processed and filtered separately. Initial filter parameters, low-cut-off and high-cut-off frequencies, are first determined by the global mean of the probability densities computed from all feature vectors of a given speech utterance. Then, the cut-off frequencies are adapted over time, i.e. every frame vector, in both low-frequency and high-frequency bands based also on the global mean and the standard deviation of feature vectors. The filtered feature vectors are used in a SVM-GMM Supervector speaker verification system. The NIST Speaker Recognition Evaluation 2006 (SRE06) core-test is used in evaluation. Experimental results show that the proposed technique clearly outperforms a baseline system using a conventional RelAtive SpecTrA (RASTA) filter.

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.

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.

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.

A design methodology for implementation of low-noise switched-capacitor low-pass filter (SC LPF) with small capacitance spread is proposed. The proposed method is focused on the reduction of operational amplifier noise transfer gain at low frequencies and the reduction of total capacitance. A new SC LPF topology is proposed in order to adapt the correlated double sampling and charge scaling technique at the same time. Design examples show that proposed filter reduces the total capacitance by 65% or more compared to the conventional one without having significant increase in noise transfer gain.

This paper presents the design of a second-order and a fourth-order bandpass filter (BPF) for 60 GHz millimeter-wave applications in 0.18 µm CMOS technology. The proposed on-chip BPFs employ the folded open loop structure designed on pattern ground shields. The adoption of a folded structure and utilization of multiple transmission zeros in the stopband permit the compact size and high selectivity for the BPF. Moreover, the pattern ground shields obviously slow down the guided waves which enable further reduction in the physical length of the resonator, and this, in turn, results in improvement of the insertion losses. A very good agreement between the electromagnetic (EM) simulations and measurement results has been achieved. As a result, the second-order BPF has the center frequency of 57.5 GHz, insertion loss of 2.77 dB, bandwidth of 14 GHz, return loss less than 27.5 dB and chip size of 650 µm810 µm (including bonding pads) while the fourth-order BPF has the center frequency of 57 GHz, insertion loss of 3.06 dB, bandwidth of 12 GHz, return loss less than 30 dB with chip size of 905 µm810 µm (including bonding pads).

Blocking artifacts are introduced in many block-based coding systems, and its reduction can significantly improve the subjective quality of compressed video. The H.264/AVC uses an in-loop deblocking filter to remove the blocking artifacts. The filter considers some coding conditions in its adaptive deblocking filtering such as coded block pattern (CBP), motion vector, macroblock type, etc. for inter-predicted blocks, however, it does not consider much for intra-coded blocks. In this paper, we utilize the human visual system (HVS) characteristic and the local characteristic of image blocks to modify the boundary strength (BS) of the intra-deblocking filter in order to gain improvement in the subjective quality and also to reduce the complexity in filtering intra coded slices. In addition, we propose a low-complexity deblocking method which utilizes the correlation between vertical and horizontal boundaries of a block in inter coded slices. Experimental results show that our proposed method achieves not only significant gain in the subjective quality but also some PSNR gain, and reduces the computational complexity of the deblocking filter by 36.23% on average.

This paper presents analysis and design of passive RC polyphase filters (RCPFs) in tutorial style. Single-phase model of a single-stage RCPF is derived, and then, multi-stage RCPFs are analyzed and obtained some restrictions for realizable poles and zeros locations of RCPFs. Exact design methods of RCPFs with equal ripple type, and Butterworth type responses are explained for transfer function design and element value design along with some design examples.

We propose a practical local and global path-planning algorithm for an autonomous vehicle or a car-like robot in an unknown semi-structured (or unstructured) environment, where obstacles are detected online by the vehicle's sensors. The algorithm utilizes a probabilistic method based on particle filters to estimate the dynamic obstacles' locations, a support vector machine to provide the critical points and Bezier curves to smooth the generated path. The generated path safely travels through various static and moving obstacles and satisfies the vehicle's movement constraints. The algorithm is implemented and verified on simulation software. Simulation results demonstrate the effectiveness of the proposed method in complicated scenarios that posit the existence of multi moving objects.