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.

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 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.

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 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).

Entity is an important information carrier in Web pages. Users would like to directly get a list of relevant entities instead of a list of documents when they submit a query to the search engine. So the research of related entity finding (REF) is a meaningful work. In this paper we investigate the most important task of REF: Entity Ranking. The wrong-type entities which don't belong to the target-entity type will pollute the ranking result. We propose a novel method to filter wrong-type entities. We focus on the acquisition of seed entities and automatically extracting the common Wikipedia categories of target-entity type. Also we demonstrate how to filter wrong-type entities using the proposed model. The experimental results show our method can filter wrong-type entities effectively and improve the results of entity ranking.

Network devices, such as routers or L3 switches, have a feature called packet-filtering for network security. They determine whether or not to pass arriving packets by applying filtering rules to them. If the number of comparisons of packets with rules increases, the time required for a determination will increase, which will result in greater communication delay. Various algorithms for optimizing filtering tables to minimize the load of packet filtering, which directly impacts the communication delay, have been proposed. In this paper, first we introduce an adaptive packet filter based on an algorithm that reconstructs the filtering table according to the frequency distribution of arrival packets. Next, we propose a new reconstruction algorithm based on grouping of dependent rules. Grouping dependent rules makes it possible to sort the rules in the table by the frequency of matching. Finally, we show the effectiveness of our algorithm by comparing it against previously reported algorithms.

In this letter, an intra-field deinterlacing algorithm based on a gradient inverse weighted filtering (GIWF) interpolator is proposed. The proposed algorithm consists of three steps: We first interpolate the missing line with simple strategies in the working window. Then we calculate the coefficients of the gradient-weighted filters by exploiting the local gray gradients among the neighboring pixels. In the last step, we interpolate the missing line using the proposed GIWF interpolator. Experiments show that the proposed algorithm provides superior performances in terms of both objective and subjective image qualities.

In this paper, we present a method to combine lapped transforms with various downsampling factors. The factor is changed depending on a local feature of a given signal, and it can be realized by using time-domain lapped transforms. In image coding application, our method maintains good image coding performance for a wide range of bitrates and fills the gap between undersampled and critically-/oversampled systems.

This paper presents a multi-band WCDMA receiver consisting of a multi-band low noise amplifier (LNA), a multi-band mixer and an inter-stage tunable notch filter. The notch filter is used to suppress Tx leakage, and 0.8–1.5 GHz (66%) of tuning range is achieved. The receiver achieves 33 and 30 dB conversion gain, 6.4 and 8 dB NF, 50 and 35.5 dBm IIP2, and -6 and -4.7 dBm IIP3 at 0.8 and 1.5 GHz, respectively. The power consumption is 121 mW from a 1.8-V power supply. The receiver is implemented in a 0.18-µm CMOS process.

This paper proposes an adaptive comb filter with flexible notch gain. It can appropriately remove a periodic noise from an observed signal. The proposed adaptive comb filter uses a simple LMS algorithm to update the notch gain coefficient for removing the noise and preserving a desired signal, simultaneously. Simulation results show the effectiveness of the proposed comb filter.

In this paper, we propose an automatic parameter adjustment method for audio equalizers using an interactive genetic algorithm (IGA). It is very difficult for ordinary users who are not familiar with audio devices to appropriately adjust the parameters of audio equalizers. We therefore propose a system that can automatically adjust the parameters of audio equalizers on the basis of user's evaluation of the reproduced sound. The proposed system utilizes an IGA to adjust the gains and Q values of the peaking filters included in audio equalizers. Listening test results demonstrate that the proposed system can appropriately adjust the parameters on the basis of the user's evaluation.

Recently a simple algorithm was presented by the first author which enables one to successively compute the transformation matrix of various order for the general 1-D to 1-D polynomial transformation. This letter extends the result to the general 1-D to 2-D polynomial transformation. It is also shown that the matrix obtained can be used for the 2-D to 2-D polynomial transformation as well.

The wireless sensor network (WSN) is a technology that senses environmental information and provides appropriate services to users. There are diverse application areas for WSNs such as disaster prevention, military, and facility management. Despite the many prospective applications, WSN s are vulnerable to various malicious attacks. In false report attacks, a malicious attacker steals a few sensor nodes and obtains security materials such as authentication keys from the nodes. The attacker then injects false event reports to the network through the captured nodes. The injected false reports confuse users or deplete the limited energy of the nodes in the network. Many filtering schemes have been proposed to detect and remove false reports. In the statistical en route filtering (SEF) scheme, each node shares authentication keys selected from a global key pool. Due to the limited memory, each node is able to store only a small portion of the global key pool. Therefore, the routing paths of the event reports significantly affect the filtering (i.e., detecting) probability of false reports. In this paper, we propose a method to determine the routing paths of event reports both hop by hop and on demand at each node. In this method, each node chooses the next node on the path from the event source to the sink node based on the key indexes of its neighbor nodes. Experiments show that the proposed method is far more energy efficient than the SEF when the false traffic ratio (FTR) is ≥ 50% in the network.

A low-complexity method for angle estimation in Multiple-input multiple-output radar (MIMO) radar is presented. In this approach, the signal subspace can be spanned by the orthogonal vectors which are obtained by Multi-stage Wiener Filter (MSWF), then the ESPRIT method can be used to estimate direction of departures (DODs) and direction of arrivals (DOAs). Compared with the conventional ESPRIT algorithm, the proposed method does not involve estimation of the covariance matrix and its eigen-decomposition, which alleviates remarkably the computational complexity. Moreover, the proposed method achieves the similar angle estimation performance. Simulation results are presented to verify the efficiency of the proposed method.

In this paper, a new skin detection method using pixel color and image regional information, intended for objectionable image filtering is proposed. The method consists of three stages: skin detection, feature extraction and image classification. Skin detection is implemented in two steps. First, a Sinc function, fitted to skin color distribution in the Cb-Cr chrominance plane is used for detecting pixels with skin color properties. Next, to benefit regional information, based on the theory of color image reproduction, it's shown that the scattering of skin pixels in the RGB color space can be approximated by an exponential function. This function is incorporated to extract the final accurate skin map of the image. As objectionable image features, new shape and direction features, along with area feature are extracted. Finally, a Multi-Layer Perceptron trained with the best set of input features is used for filtering images. Experimental results on a dataset of 1600 images illustrate that the regional method improves the pixel-based skin detection rate by 10%. The final classification result with 94.12% accuracy showed better results when compared to other methods.

The power of laser radar received echoes varies over a large range due to many factors such as target distance, size, reflection ratio, etc, which leads to the difficulty of decoding codes from the received noise buried signals for spectrum code modulated laser radar. Firstly, a pseudo-random noise (PN) code modulated laser radar model is given, and the problem to be addressed is discussed. Then, a novel method based on Inter Symbol Interference (ISI) is proposed for resolving the problem, providing that only Additive White Gaussian Noise (AWGN) exists. The ISI effect is introduced by using a high pass filter (HPF). The results show that ISI improves laser radar receiver decoding ratio, thus the peak of the correlation function of decoded codes and modulation codes. Finally, the effect of proposed method is verified by a simple experiment.

In this paper, a novel charge coupled device matched filter (CCD-MF) for Electrical code division multiplexing (ECDM) decoder is proposed and experimentally demonstrated. Simulation results clarify the influence of low charge transfer efficiency (CTE) and the validity of a parallel CCD-MF we proposed. A 15-channel ECDM system using a 2 Gchip/s, 2-parallel CCD-MF is experimentally demonstrated.

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.