Output Samples Research Articles

Research on Key Problems of Channel Estimation Based on Plural RBF Neural Network

A new channel estimation method of neural network based on complex radial basis function (CRBF) is proposed to enhance the anti-interference ability of traditional pilot frequency estimation algorithm in power line communication (PLC). This method builds up a new channel model of complex field signals in PLC. The complete response model was established by using transmitting terminal’s pilot signal as input sample data, pilot signal’s frequency response as output sample data, and pre-setting mean square error (MSE) and diffusion constant. Computer simulations show that compared with the traditional algorithm the channel estimation was more accurate and had lower MSE and bit error rate (BER).

REDUCED ORDER EXTENDED STATE OBSERVER WITHOUT OUTPUT DERIVATIVE IN ADRC

As an observer based method; the ESO in ADRC introduces more phase lag when the observer order becomes higher. The key detriment of phase lag is the reduction of loop stability. A way to decrease the phase lag is to employ a RESO. Nevertheless, the underlying disadvantage of this approach is that RESO computation depends on output derivative. To overcome this problem, the derivative of the output is usually approximated from the difference of two neighbouring output sample values. However, this approach is not convenient for two raisons. First, the use of simple differences to derive the output is another source of phase lag. Second, observers are particularly sensitive to noise and derivative gains amplify noise increasing the sensitivity of the RESO. In this work, it is employed a method to obtain a RESO that does not depend on the output derivative. It is also developed the reduced order version of the GESO.

The Table-Hadamard GRNG

Gaussian random number generators (GRNGs) are an important component in parallel Monte Carlo simulations using FPGAs, where tens or hundreds of high-quality Gaussian samples must be generated per cycle using very few logic resources. This article describes the Table-Hadamard generator, which is a GRNG designed to generate multiple streams of random numbers in parallel. It uses discrete table distributions to generate pseudo-Gaussian base samples, then a parallel Hadamard transform to efficiently apply the central limit theorem. When generating 64 output samples, the Table-Hadamard requires just 130 slices per generated sample, which is a third of the resources needed by the next best technique, while still providing higher statistical quality.

The Performance of Advanced Sequencing Batch Reactor in Wastewater Treatment Plant to Remove Organic Materials and Linear Alkyl Benzene Sulfonates

Background: Linear alkyl benzene sulfonates (LAS) are the most important ionic detergents that produce negative ions in the environment. These compounds enter surface waters through domestic and industrial wastewaters and cause environmental hazards. Objectives: The present study was aimed at assessing the performance of advanced sequencing batch reactor (SBR) in wastewater treatment plant of Yazd, Iran, to remove organic materials and detergents. Materials and Methods: The present research was a descriptive longitudinal study conducted on 96 input and output samples of SBR system over eight months from October 2012 to June 2013. The studied parameters were biochemical oxygen demand 5 (BOD5), chemical oxygen demand (COD), and detergents (LAS), which were assessed through standard methods. Finally, the study data were analyzed through analysis of variance (ANOVA) using software package for statistical analysis (SPSS). Results: The mean inputs of BOD5, COD, and LAS to the SBR system were 292.40 ± 45.28, 597.15 ± 97.30, and 3.29 ± 0.92 mg/L, and the mean outputs were 20.59 ± 3.54, 59.34 ± 9.47, and 0.606 ± 0.09 mg/L, respectively. The removal efficiency of BOD5, COD and LAS were respectively 92.95%, 90.06% and 81.6%. The results of ANOVA indicated that there was a significant relationship between the mean inputs and outputs of BOD5, COD, and the detergents (P ≤ 0.001). Conclusions: With the proper operation of wastewater the treatment plant and increasing the retention time, the removal efficiency of the detergents increased. In addition, according to the environmental standards for BOD5, COD and the detergents, the results of the present study indicated that the outputs of these parameters from the SBR system were appropriate for agricultural irrigation.

Identification of linear continuous-time systems under irregular and random output sampling

This paper considers the problem of identifiability and parameter estimation of single-input–single-output, linear, time-invariant, stable, continuous-time systems under irregular and random sampling schemes. Conditions for system identifiability are established under inputs of exponential polynomial types and a tight bound on sampling density. Identification algorithms of Gauss–Newton iterative types are developed to generate convergent estimates. When the sampled output is corrupted by observation noises, input design, sampling times, and convergent algorithms are intertwined. Persistent excitation (PE) conditions for strongly convergent algorithms are derived. Unlike the traditional identification, the PE conditions under irregular and random sampling involve both sampling times and input values. Under the given PE conditions, iterative and recursive algorithms are developed to estimate the original continuous-time system parameters. The corresponding convergence results are obtained. Several simulation examples are provided to verify the theoretical results.

Polo camiño, polo camiño adiante e camiño adiante, tres fórmulas do locativo por onde en galego

Este artigo propón unha análise do funcionamento das construcións tipo camiño adiante, isto é, a xuntanza dun substantivo e dun adverbio para indicar lugar por onde. Esta fórmula concorre, en desvantaxe no uso, con outras estruturas para expresar a dita indicación locativa, de maneira que para coñecer e entender o funcionamento da primeira debemos ter unha visión en contraste coas outras. Para desenvolver esta investigación baseámonos nun traballo de análise de corpus con rexistros extraídos de producións lingüísticas reais tiradas do Tesouro Informático da Lingua Galega. A visión contrastiva levounos a percibir que as diferentes opcións funcionan como un contínuum que ten os seus estremos na construción con preposición por (polo camiño) —presentándose esta como a fórmula non marcada para indicar lugar por onde— e o acusativo locativo (dentro do esquema argumental de verbos de movemento transitivos, colleu o camiño). Nos estadios intermedios encontraríase a estrutura que é o obxecto do noso estudo e unha intermedia coa que comparte moitos aspectos do seu funcionamento: polo camiño adiante. Aínda encadrándose nun contínuum construtivo, ou xustamente por poderen ser explicadas deste modo, cada unha das alternativas das que dispón a falante conta coas súas especificidades construtivas e tampouco son absolutamente equivalentes a respecto da información que transmiten.

Analytical modeling of activation procedure applied in α-alumina thermo-mechanical synthesis

The impact of the mechanical processing parameters on the alumina grain-size distribution affiliated characteristics and on the γ to α phase transformation rate was investigated. The moderation in the alumina samples behavior has been correlated to the granulometric and mineralogical changes induced by activation via an ultra-centrifugal mill. The assessment of the activation process variables influence on the final quality of the product parameters was conveyed in order to optimize the mechanical treatment of the alumina, which otherwise could be regarded as either energetically or economically unsustainable procedure. The Response Surface Method, Standard Score Analysis and Principal Component Analysis were applied as means of the mechanical activation optimization. The r2 values obtained by developed models were in range from 0.816 to 0.988. The established mathematical models were able to precisely predict the quality parameters in a broad range of processing parameters. The Standard Score Analysis emphasized that the optimal output sample was obtained using a sieve mesh of 120μm set of processing parameters (SS=0.96). Diverse comparison analyses disclosed that the optimal set of activation process parameters could reduce the negative effect of γ-alumina samples immanent properties on the final score, and furthermore to enhance the rate of γ to α transition which would improve energetic and economic sustainability of the alumina phase transformation procedure.

A Metacognitive Fully Complex Valued Functional Link Network for solving real valued classification problems

In this paper, a sequential learning based meta-cognitive fully complex valued functional link network (Mc-FCFLN) is developed for solving complex real world problems. Mc-FCFLN network consists of two components: a cognitive component and a meta-cognitive one. A fully complex-valued functional link network (FCFLN) is a cognitive component and the self-regulatory learning method is its meta-cognitive component. As the network does not possess hidden layers, the multi-variable polynomials are represented in the input layer for capturing the nonlinear relationship between the input and the output sample. Moreover, when the sample is presented to the Mc-FCFLN network, the meta-cognitive component decides what to learn, when to learn, and how to learn depending on the knowledge gained by the FCFLN network and the novel information present in the sample. The network can learn sample one after the other and thus the drawback existing with the batch learning strategy can be eliminated while orthogonal least square principle is used for selecting the best polynomial and the recursive least square update is used for tuning the network. Multi-category and binary datasets chosen from the UCI machine learning repository is used for the validation of the proposed classifier. Lastly, a performance comparison of the Mc-FCFLN applied for classification problems shows better classification ability when compared with the other existing classifiers in the literature.

Behavior, distribution and environmental influence of arsenic in a typical lead smelter

A field study was conducted to determine the behavior and distribution of arsenic during the pyrometallurgy process in a typical SKS (Shuikoushan) lead smelter in Hunan province, China. Environmental influences of arsenic in selected samples were evaluated. Arsenic contents in all input and output samples vary from 0.11% in raw lead to 6.66% in collected dust-2. More arsenic is volatilized in blast furnace and fuming furnace (73.02% of arsenic input) than bottom blowing furnace (10.29% of arsenic input). There are 78.97%, 13.69%, 7.31% of total arsenic distributed in intermediate materials, stockpiled materials and unorganized emissions, respectively. Matte slag-2, collected dust-1 and secondary zinc oxide are hazardous based on the arsenic concentrations of toxicity characteristic leaching procedure. According to risk assessment code (RAC) guideline, arsenic in collected dust-1 poses a very serious risk to the surrounding environment, arsenic in speiss, matte slag-2, water-quenched slag and secondary zinc oxide show low risk, while arsenic in matte slag-1, collected dust-2 and post dust has no risk to the environment.

ASCORBIC ACID DEGRADATION KINETIC FOR MICROWAVE DRIED BASIL, PURSLANE AND CELERY LEAVES

In this study, the goal was to evaluate the ascorbic acid degradation in basil, purslane and celery leaves during microwave drying. The effects of microwave output power and sample amount on ascorbic acid loss in basil, purslane and celery leaves were investigated. The method for the determination of ascorbic acid content was based on the reaction between ascorbic acid and 2,6-dichloroindophenol and was successfully applied to basil, purslane and celery leaves. Increasing microwave output power and decreasing sample amount led to higher degradation rates in basil, purslane and celery leaves. Ascorbic acid degradation kinetics in basil, purslane and celery leaves during microwave drying followed a first-order reaction. The activation energy values were also calculated using an exponential expression based on Arrhenius equation for degradation of ascorbic acid.

Improved detection of extended spectrum beta-lactamase (ESBL)-producing Escherichia coli in input and output samples of German biogas plants by a selective pre-enrichment procedure.

The presence of extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli was investigated in input (manure from livestock husbandry) and output samples of six German biogas plants in 2012 (one sampling per biogas plant) and two German biogas plants investigated in an annual cycle four times in 2013/2014. ESBL-producing Escherichia coli were cultured by direct plating on CHROMagar ESBL from input samples in the range of 100 to 104 colony forming units (CFU) per g dry weight but not from output sample. This initially indicated a complete elimination of ESBL-producing E. coli by the biogas plant process. Detected non target bacteria were assigned to the genera Acinetobacter, Pseudomonas, Bordetella, Achromobacter, Castellaniella, and Ochrobactrum. A selective pre-enrichment procedure increased the detection efficiency of ESBL-producing E. coli in input samples and enabled the detection in five of eight analyzed output samples. In total 119 ESBL-producing E. coli were isolated from input and 46 from output samples. Most of the E. coli isolates carried CTX-M-type and/or TEM-type beta lactamases (94%), few SHV-type beta lactamase (6%). Sixty-four bla CTX-M genes were characterized more detailed and assigned mainly to CTX-M-groups 1 (85%) and 9 (13%), and one to group 2. Phylogenetic grouping of 80 E. coli isolates showed that most were assigned to group A (71%) and B1 (27%), only one to group D (2%). Genomic fingerprinting and multilocus sequence typing (MLST) showed a high clonal diversity with 41 BOX-types and 19 ST-types. The two most common ST-types were ST410 and ST1210. Antimicrobial susceptibility testing of 46 selected ESBL-producing E. coli revealed that several isolates were additionally resistant to other veterinary relevant antibiotics and some grew on CHROMagar STEC but shiga-like toxine (SLT) genes were not detected. Resistance to carbapenems was not detected. In summary the study showed for the first time the presence of ESBL-producing E. coli in output samples of German biogas plants.

Estimation of channel mismatches in time-interleaved analog-to-digital converters based on fractional delay and sine curve fitting

This paper proposes an algorithm to estimate the channel mismatches in time-interleaved analog-to-digital converter (TIADC) based on fractional delay (FD) and sine curve fitting. Choose one channel as the reference channel and apply FD to the output samples of reference channel to obtain the ideal samples of non-reference channels with no mismatches. Based on least square method, the sine curves are adopted to fit the ideal and the actual samples of non-reference channels, and then the mismatch parameters can be estimated by comparing the ideal sine curves and the actual ones. The principle of this algorithm is simple and easily understood. Moreover, its implementation needs no extra circuits, lowering the hardware cost. Simulation results show that the estimation accuracy of this algorithm can be controlled within 2%. Finally, the practicability of this algorithm is verified by the measurement results of channel mismatch errors of a two-channel TIADC prototype.

Frequency Response Function Estimation in the Presence of Missing Output Data

Frequency response function (FRF) estimation is part of nonparametric system identification in the frequency domain. The FRF measurements give a quick but deep insight into the dynamics of complex systems. Data samples can get lost in some applications due to sensor failure and/or data transmission errors. We want to overcome this problem without having to repeat the measurement and/or the experiment because this can be either impossible or too expensive. In this paper, we propose a nonparametric method for estimating the FRF and its variance of a single-input single-output system from known input and noisy output measurements with missing output samples. No particular pattern of the missing data is assumed. Moreover, the proposed method provides an estimate of the missing data and its uncertainty.

Improved extreme learning machine for multivariate time series online sequential prediction

Multivariate time series has attracted increasing attention due to its rich dynamic information of the underlying systems. This paper presents an improved extreme learning machine for online sequential prediction of multivariate time series. The multivariate time series is first phase-space reconstructed to form the input and output samples. Extreme learning machine, which has simple structure and good performance, is used as prediction model. On the basis of the specific network function of extreme learning machine, an improved Levenberg–Marquardt algorithm, in which Hessian matrix and gradient vector are calculated iteratively, is developed to implement online sequential prediction. Finally, simulation results of artificial and real-world multivariate time series are provided to substantiate the effectiveness of the proposed method.

A general multirate approach for direct closed-loop identification to the Nyquist frequency and beyond

Without injecting any external persistently exciting signals, a general multirate approach is proposed for direct closed-loop identification. First, an extended least-squares algorithm is designed to identify the mixed-rate model after polynomial transformation. Next, the identified mixed-rate model is used to compute the fast-rate model, from which system dynamics to the Nyquist frequency and beyond can be obtained. Identifiability is mathematically proven if the plant output sampling rate is non-integer multiples of the controller sampling rate. The effectiveness of the proposed approach is evaluated by both the simulation and experimental results in a hard disk drive.

Multirate Output Feedback with Discrete Time Sliding Mode Control for Inverted Pendulum System

In this paper, a multirate output feedback (MROF) based on discrete time sliding mode control (DSMC) method is proposed. The MROF controller is designed to maintain the inverted pendulum at upright position by controlling the tracking position of a cart. This method is practical because it only used the output samples and the measurement of the system states feedback is not necessary. The MROF output sampling is used to estimate the unmeasured states and subsequently applied to the uncertain system. The simulation results validated the advantages of the proposed controller despite the existence of nonlinearities in inverted pendulum system.

Minimum Phase Property of Chebyshev-Sharpened Cosine Filters

We prove that the Chebyshev sharpening technique, recently introduced in literature, provides filters with a Minimum Phase (MP) characteristic when it is applied to cosine filters. Additionally, we demonstrate that cascaded expanded Chebyshev-Sharpened Cosine Filters (CSCFs) are also MP filters, and we show that they achieve a lower group delay for similar magnitude characteristics in comparison with traditional cascaded expanded cosine filters. The importance of the characteristics of cascaded expanded CSCFs is also elaborated. The developed examples show improvements in the group delay ranged from 23% to 47% at the cost of a slight increase of usage of hardware resources. For an application of a low-delay decimation filter, the proposed scheme exhibits a 24% lower group delay, with 35% less computational complexity (estimated in Additions per Output Sample) and slightly less usage of hardware elements.

An input-balanced realization-based structure for efficient implementation of digital IIR filters

Based on an input-balanced state-space realization, this paper derives a novel structure for efficient implementation of digital IIR filters. Such a structure is very similar to a normalized lattice and, for an N th order IIR filter, it possesses 5 N -1 non-trivial multipliers: two multipliers less than in a normalized lattice. Expressions for transfer function sensitivity measures and roundoff noise gain for the proposed structure are derived. Interestingly, it is shown that, when the filter is all-pass, the proposed structure requires 4 N multiplications in order to compute one output sample. Moreover, the corresponding roundoff noise gain is 4 N , much smaller than that of ( N +1) 2 given by the classical minimum roundoff state-space realizations. Results of simulations performed show that the proposed structure outperforms many classical ones in terms of implementation efficiency and robustness against finite-word-length effects.

Perceptual Subspace Speech Enhancement with Variance Normalization

In this paper a perceptual subspace speech enhancement method using masking property of human auditory system with variance normalization is presented. The masking property of the human auditory system is used while deciding the gain parameters for the algorithm. Spectral Domain Constrained estimator was employed in determining the filter coefficients and colored noise was handled by replacing the noise variance by Rayleigh quotient. Variance normalization is further done to remove the spikes in the values so as to avoid abrupt increase or decrease in power of the output samples making the output more intelligible. The objective measures SNRLoss and SNRLESC were chosen for performance evaluation based on their efficiency in determining the intelligibility of the output. The results show an improved performance of the proposed method over some of the existing speech enhancement methods in terms of intelligibility.

Discrete-Time Nonlinear Control of VSC-HVDC System

Because VSC-HVDC is a kind of strong nonlinear, coupling, and multi-input multioutput (MIMO) system, its control problem is always attracting much attention from scholars. And a lot of papers have done research on its control strategy in the continuous-time domain. But the control system is implemented through the computer discrete sampling in practical engineering. It is necessary to study the mathematical model and control algorithm in the discrete-time domain. The discrete mathematical model based on output feedback linearization and discrete sliding mode control algorithm is proposed in this paper. And to ensure the effectiveness of the control system in the quasi sliding mode state, the fast output sampling method is used in the output feedback. The results from simulation experiment in MATLAB/SIMULINK prove that the proposed discrete control algorithm can make the VSC-HVDC system have good static, dynamic, and robust characteristics in discrete-time domain.