Pass Filter Research Articles

A Multiple Frequency Band Watermarking Algorithm Based on Stripe Image

In this paper, a multiple frequency band watermarking algorithm based on stripe image is proposed. The algorithm converts watermark string representing the copyright of image works to stripe image before embedding it to host image. Because of the error correction ability of the stripe image, the algorithm takes on high robustness. This paper also proposed a multiple frequency band embedding strategy through analyzing and classifying various watermark attacking algorithm. Applying this algorithm, watermark can stand several kinds of attacks such as low pass filter and high pass filter. Experimental results show that a blind watermarking algorithm with high robustness to various watermark attacking can be achieved through combining stripe image coding and multiple frequency band strategy.

Applied-Information Technology with Method of Digital Image Noise Processing

Digital image processing is a kind of technology which employs a certain algorithm to realize image processing through computer algorithm. The powerful capacity of computing and graphics displaying function of Matlab makes image processing becomes more simple and intuitive. This paper introduces the basic knowledge of dealing with noise in digital image, expounds the neighborhood average method, median filtering in detail, and low pass filtering and other typical of eliminating noise method , and at the same time analyzes and compares the characteristics of several typical methods by use of the software Matlab.

Digital Stable IIR Band Pass Filter Design Using Seeker Optimization Technique

This paper presents a novel, control parameter independent evolutionary search technique known as Seeker Optimization Algorithm (SOA) for the design of a eighth order Infinite Impulse Response (IIR) Band Pass (BP) filter. A new fitness function has also been adopted in this paper to improve the stop band attenuation to a great extent. The performance of the SOA based IIR BP filter design has proven to be much superior as compared to those obtained by real coded genetic algorithm (RGA) and standard particle swarm optimization (PSO) in terms of highest sharpness at cut-off, smallest pass band ripple, highest stop band attenuation, smallest stop band ripple and also the fastest convergence speed with assured stability recognized by the pole-zero analysis of the designed optimized IIR filter.

Common-mode suppressed differential bandpass filter based on open complementary split ring resonators fabricated in microstrip technology without ground plane etching

A differential (or balanced) bandpass filter based on open complementary split ring resonators (OCSRRs) coupled through admittance inverters is presented in this article. Pairs of OCSRRs are symmetrically placed in a mirror configuration between the strips of the differential line and are modeled by means of two series connected parallel resonators. For the differential (odd) mode, there is a virtual ground at the connecting plane between the OCSRR pairs, and the structure is roughly described by the canonical model of a bandpass filter, consisting of a cascade of shunt resonators coupled through admittance inverters. It is demonstrated that, through a proper design of the OCSRR stages, the common mode noise in the vicinity of the differential filter pass band can be efficiently suppressed. Due to the differential mode operation of the filter, it is not necessary to incorporate metallic vias to ground the OCSRRs. Moreover, as compared to other differential filters based on OCSRRs, defected ground structures are not present in the proposed filters. To illustrate the potential of the approach, two balanced bandpass filters are designed, fabricated, and characterized. © 2014 Wiley Periodicals, Inc. Microwave Opt Technol Lett 56:910–916, 2014

Ischaemic Strokes in Patients with Pulmonary Arteriovenous Malformations and Hereditary Hemorrhagic Telangiectasia: Associations with Iron Deficiency and Platelets

BackgroundPulmonary first pass filtration of particles marginally exceeding ∼7 µm (the size of a red blood cell) is used routinely in diagnostics, and allows cellular aggregates forming or entering the circulation in the preceding cardiac cycle to lodge safely in pulmonary capillaries/arterioles. Pulmonary arteriovenous malformations compromise capillary bed filtration, and are commonly associated with ischaemic stroke. Cohorts with CT-scan evident malformations associated with the highest contrast echocardiographic shunt grades are known to be at higher stroke risk. Our goal was to identify within this broad grouping, which patients were at higher risk of stroke.Methodology497 consecutive patients with CT-proven pulmonary arteriovenous malformations due to hereditary haemorrhagic telangiectasia were studied. Relationships with radiologically-confirmed clinical ischaemic stroke were examined using logistic regression, receiver operating characteristic analyses, and platelet studies.Principal FindingsSixty-one individuals (12.3%) had acute, non-iatrogenic ischaemic clinical strokes at a median age of 52 (IQR 41–63) years. In crude and age-adjusted logistic regression, stroke risk was associated not with venous thromboemboli or conventional neurovascular risk factors, but with low serum iron (adjusted odds ratio 0.96 [95% confidence intervals 0.92, 1.00]), and more weakly with low oxygen saturations reflecting a larger right-to-left shunt (adjusted OR 0.96 [0.92, 1.01]). For the same pulmonary arteriovenous malformations, the stroke risk would approximately double with serum iron 6 µmol/L compared to mid-normal range (7–27 µmol/L). Platelet studies confirmed overlooked data that iron deficiency is associated with exuberant platelet aggregation to serotonin (5HT), correcting following iron treatment. By MANOVA, adjusting for participant and 5HT, iron or ferritin explained 14% of the variance in log-transformed aggregation-rate (p = 0.039/p = 0.021).SignificanceThese data suggest that patients with compromised pulmonary capillary filtration due to pulmonary arteriovenous malformations are at increased risk of ischaemic stroke if they are iron deficient, and that mechanisms are likely to include enhanced aggregation of circulating platelets.

Evaluation of dissimilar friction stir lap joints using digital X-ray radiography

A digital X-ray radiography methodology is proposed for quality assessment of aluminium–zinc coated steel dissimilar lap joints produced by a friction stir welding process. This methodology uses digital frame integration for acquisition of data to reduce the image noise followed by high pass filtering to sharpen the image by gradient operation and contrast adjustments to detect micro defects in FSW joints. The effect of welding parameters such as rotational and travel speed of weld tool and penetration depth on quality of the weld is studied. The new methodology has resulted in three-fold increase in signal-to-noise ratio (SNR) with improved defect detection sensitivity. The present study clearly shows that the weld tool rotational speed, travel speed and plunger depth have a decisive role on the quality of the weld obtained by the friction stir welding process.

An efficient differential evolution with wavelet mutation algorithm for optimal IIR filter design

In this paper, an improved version of differential evolution (DE) algorithm which incorporates wavelet-based mutation strategy called differential evolution with wavelet mutation (DEWM) is proposed for the design of digital infinite impulse response (IIR) filters. Unlike fixed value of scaling factor in standard DE, the proposed optimisation technique DEWM adopts iteration dependent scaling factor governed by the wavelet function during the mutation process. This modification in the mutation process not only ensures the faster searching in the multidimensional search space but also the solution produced is very close to the global optimal solution. The effectiveness of this algorithm is justified with a comparative study of some well established algorithms, namely, real coded genetic algorithm (RGA), conventional particle swarm optimisation (PSO) and standard DE with a superior DEWM-based outcome for the designed 8th order IIR low pass (LP), high pass (HP), band pass (BP) and band stop (BS) filters. Simulation results affirm that the proposed DEWM algorithm outperforms its counterparts not only in terms of quality output, i.e., sharpness at cut-off, pass band ripple and stop band attenuation but also in convergence speed with assured stability.

CFOA Based Low Pass and High Pass Ladder Filter—A New Configuration

A new technique using signal flow graph for conversion of ladder based filter into CFOA based filter has been proposed. The proposed technique converts the existing LC ladder based filter into CFOA in low pass and high pass configuration. The design of low pass filter and high pass filter has been realized using the proposed technique. The proposed configuration is implemented using CFOA as an active device and all the capacitors are grounded. Simulation has been carried out using simulation software I-cap. The simulation results have been demonstrated and discussed.

Investigating recurrent neural networks for OCT A-scan based tissue analysis.

Optical Coherence Tomography (OCT) has been proposed as a high resolution image modality to guide transbronchial biopsies. In this study we address the question, whether individual A-scans obtained in needle direction can contribute to the identification of pulmonary nodules. OCT A-scans from freshly resected human lung tissue specimen were recorded through a customized needle with an embedded optical fiber. Bidirectional Long Short Term Memory networks (BLSTMs) were trained on randomly distributed training and test sets of the acquired A-scans. Patient specific training and different pre-processing steps were evaluated. Classification rates from 67.5% up to 76% were archived for different training scenarios. Sensitivity and specificity were highest for a patient specific training with 0.87 and 0.85. Low pass filtering decreased the accuracy from 73.2% on a reference distribution to 62.2% for higher cutoff frequencies and to 56% for lower cutoff frequencies. The results indicate that a grey value based classification is feasible and may provide additional information for diagnosis and navigation. Furthermore, the experiments show patient specific signal properties and indicate that the lower and upper parts of the frequency spectrum contribute to the classification.

Nonstationary signal pattern recognition using fast time-time filtering and decision tree

This paper proposes a fast Time-Time (TT) filtering transform for analysis and pattern recognition of nonstationary signals. A fast TTtransform algorithm is developed with different types of frequency scaling, band pass filtering and interpolation techniques to reduce the computational cost. The new time-time transform uses dyadic and selective scaling that facilitates the extraction of relevant features from time-varying signals for recognizing their patterns. The extracted features are then passed through a decision tree based classifier for the identification of the signal patterns. Various real world simultaneous power signal disturbances have been simulated to prove the efficiency of the technique. The simulation results show superior performance of the new TT-Transform while classifying overlapping disturbance patterns. Because of the new fast TT – transform algorithm and a relatively simpler classifier methodology, this technique can be used for real time localization, detection, and classification of various power quality events including other nonstationary signal time series belonging to speech, biomedical signals, etc.

A new time-frequency approach for hybrid differential and impedance protection of transmission lines

A new current differential protection of transmission lines is presented in this paper using an S–transform variant having very fast computational speed suitable for real–time applications. The conventional S–transform used earlier for transmission line protection has large computational overhead and thus is not suitable for generating decisions regarding the occurrence of a fault and its type on a transmission line. The new S–transform variant is based on different types of frequency scaling, band pass filtering, and interpolation techniques to achieve a significant reduction of computation time in comparison to the original S–transform. For wide area protection as in the case of smart grid the current differential protection is realised by extracting the relevant features from the current signals at both the sending end and receiving end terminals from the new S–transform generated contours. This paper focuses on the fault detection, classification, and location aspects using a new S–transform variant applied to synchronised measurement of the differential and average energy of current signals. Digital simulation results using EMTP for a long distance transmission line show the computational speed and efficiency of this new algorithm.

Modeling and effect of distortion product generated by harmonic complex tones

To study deeply the effect of distortion product on auditory perception, a functional model is proposed to generate distortion products at frequencies below those of primary stimuli. The operations include calculating different power of the stimuli, low pass filtering, searching optimum weights, and summing the weighted signals across all filtering channels. The model uses simulate annealing and genetic algorithm to search the globally optimum weights. Moreover, this paper studies the effect of distortion products on pitch perception for unresolved harmonics based on the proposed model. Results find that distortion products could enhance the resolvability and temporal information of the harmonics. Thus, it is suggested to use background noise with appropriate sound levels to mask distortion products to reduce the effect on pitch perception.

Stator resistance estimator for direct torque control of permanent magnet synchronous motor drive systems using multi-resolution analysis wavelet

This paper presents an innovative technique for stator resistance estimation of direct torque control permanent magnet synchronous motor based on multi-resolution analysis wavelet PI controller. The online stator resistance estimation employed adjusts precisely the stator resistance value relatively to the evolution of the stator current estimation error gradient to avoid the drive instability and ensure the tracking of the actual value of the stator resistance. The multi-resolution wavelet PI controller implemented for the three level wavelet decomposition is computationally far simpler as compared to the multi-resolution technique with separate computations for high and low pass filtering at each level of decomposition. Also it is prominent by less number of tuning constants and less tuning effort as compared to a standard multi-resolution wavelet controller. The simulation results show that the proposed method can reduce the torque ripple and current ripple, superior to track the actual value of the stator resistance for different operating conditions.

Research on Digital Filter Design for Orthogonal Decomposition Algorithm Applied in Coriolis Flow Meters

Coriolis flow meters are used in measuring flow amount of natural gas and oil due to the good performance and high precision. Orthogonal decomposition algorithm is the most efficient algorithm with the highest precision in processing the digital signals of Coriolis flow meters, and digital filter design is vital important in the algorithm. In this paper we introduce a digital filter system combining the self-adaptive lattice notch filter and low pass filter embedded with Hanning Window or Kaiser Window, we also discussed the parameters selection and adjusting method deeply and systematically. For self-adaptive lattice notch filter, we calculate the key feedback parameter ρ based on bandwidth BW, leading the relative error of frequency calculated within 0.01%. For low pass digital filter, we adjust the filter order through monitoring the sine feature of the orthogonal component that has passed the low pass filter, and the relative errors of phase difference are within 0.1%. We also demonstrate the feasibility of this system through simulation under MATALAB system and calculating experiments data of Coriolis flow meter.

CRLH 전송선로를 이용한 초광대역 대역통과 필터의 설계 및 구현

A novel design method of ultra wideband based on the composite right-/left handed (CRLH) transmission line is presented in this paper. Defected ground structure and microstrip interdigital coupler are used to implement the CRLH transmission line. The proposed CRLH transmission line in this paper have composite characteristics of low pass filter and high pass filter, also it has good advantages of low insertion loss and ultra wide passband characteristics. The structure with different cell number are studied, and the UWB filter using 3-cell CRLH transmission line is fabricated and measured, which shows a good agreement between simulated and measured results. It has center frequency of 5 GHz, fractional bandwidth of 105 %, and insertion loss of 0.7 dB at center frequency.

DNA Damage Processing by Human 8-Oxoguanine-DNA Glycosylase Mutants with the Occluded Active Site

8-Oxoguanine-DNA glycosylase (OGG1) removes premutagenic lesion 8-oxoguanine (8-oxo-G) from DNA and then nicks the nascent abasic (apurinic/apyrimidinic) site by β-elimination. Although the structure of OGG1 bound to damaged DNA is known, the dynamic aspects of 8-oxo-G recognition are not well understood. To comprehend the mechanisms of substrate recognition and processing, we have constructed OGG1 mutants with the active site occluded by replacement of Cys-253, which forms a wall of the base-binding pocket, with bulky leucine or isoleucine. The conformational dynamics of OGG1 mutants were characterized by single-turnover kinetics and stopped-flow kinetics with fluorescent detection. Additionally, the conformational mobility of wild type and the mutant OGG1 substrate complex was assessed using molecular dynamics simulations. Although pocket occlusion distorted the active site and greatly decreased the catalytic activity of OGG1, it did not fully prevent processing of 8-oxo-G and apurinic/apyrimidinic sites. Both mutants were notably stimulated in the presence of free 8-bromoguanine, indicating that this base can bind to the distorted OGG1 and facilitate β-elimination. The results agree with the concept of enzyme plasticity, suggesting that the active site of OGG1 is flexible enough to compensate partially for distortions caused by mutation.

Window Size Zooming for Lower Resolution Contents

The principle main goal of the image zooming technique is to fit a smaller (or larger) images to larger (or smaller) sized display device. In order to satisfy this operation, image zooming technique must be able to alter the image size to the other one. The proposed method consists of four steps. They are ‘obtain original image,’ ‘image downscaling by image zooming,’ ‘artifact removal process by circle shaped low pass filtering,’ and ‘detail preserving process by unsharp masking.’ The simulation results approve that the proposed method removed blocking artifact and remained image details in a prosperous manner.

Programmable Gain Amplifiers with DC Suppression and Low Output Offset for Bioelectric Sensors

DC-offset and DC-suppression are key parameters in bioelectric amplifiers. However, specific DC analyses are not often explained. Several factors influence the DC-budget: the programmable gain, the programmable cut-off frequencies for high pass filtering and, the low cut-off values and the capacitor blocking issues involved. A new intermediate stage is proposed to address the DC problem entirely. Two implementations were tested. The stage is composed of a programmable gain amplifier (PGA) with DC-rejection and low output offset. Cut-off frequencies are selectable and values from 0.016 to 31.83 Hz were tested, and the capacitor deblocking is embedded in the design. Hence, this PGA delivers most of the required gain with constant low output offset, notwithstanding the gain or cut-off frequency selected.

Image Denoising in Frequency Domain Based on Analogical Basis Deconstruction

In acquisition and transmission procedures, images are often contaminated by noise in spatial and frequency domain. Image denoising is usually the first step in information extraction. At present there are many frequency domain denoising methods like low pass and high pass filtering but have not yet attained a desirable level. In this paper, we proposed a new denoising method based on Analogical Basis Deconstruction (ABD) theory. It uses only uncontaminated or slightly contaminated frequency data to recover the image through Asymptotic Iterative Estimate (AIE) algorithm. The performance of new method was tested on a simulation image and compared with the traditional frequency domain methods.

Classification of Ischemic Optic Neuropathy Using Custom Image Processing Algorithm-Statistical Based Analysis

Ischemic optic neuropathy (ION), is one of the most well-known disease which could lead to vision loss or blindness. ION impacts the head of the optic nerve (ONH),referred to as anterior (AION), and the other parts of the optic nerve, referred to as posterior (PION).This article presents a customized image processing method based on low pass filtration and segmentation of the area around the ONH , which is the region of interest (ROI) to detect ION. The extracted RIOs features for the optic nerve were analyzed and employed by statistical analysis's such as descriptive analysis and test of hypothesis. To test the sensitivity of the proposed imaging method to discriminate images of individuals with ION from healthy ones, 76 fluorescein angiography images were analyzed. The images were classified based on participants status such as: healthy, ION over the age of 45, ION under the age of 45. The proposed method demonstrated a 95% accuracy in discriminating healthy images from those with ION, and consequently would help identify the clinical features of ION.