Search results for: Fast Cosine Transform

Authors: Sherif. S. Nafee, Ameer. K. Al-Ramady, Salem. A. Shaheen

Abstract:

The analytical prediction of the decay heat results from the fast neutron fission of actinides was initiated under a project, 10-MAT1134-3, funded by king Abdulaziz City of Science and Technology (KASCT), Long-Term Comprehensive National Plan for Science, Technology and Innovations, managed by a team from King Abdulaziz University (KAU), Saudi Arabia, and supervised by Argonne National Laboratory (ANL) has collaborated with KAU's team to assist in the computational analysis. In this paper, the numerical solution of coupled linear differential equations that describe the decays and buildups of minor fission product MFA, has been used to predict the total decay heat and its components from the fast neutron fission of 235U and 239Pu. The reliability of the present approach is illustrated via systematic comparisons with the measurements reported by the University of Tokyo, in YAYOI reactor.

Keywords: Decay heat, fast neutron fission, and Numerical Solution of Linear Differential Equations.

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Authors: Chun-Yao Lee, Yao-chen Lee

Abstract:

This paper describes a method of signal process applied on an end effects of Hilbert-Huang transform (HHT) to provide an improvement in the reality of spectrum. The method is based on back-propagation network (BPN). To improve the effect, the end extension of the original signal is obtained by back-propagation network. A full waveform including origin and its extension is decomposed by using empirical mode decomposition (EMD) to obtain intrinsic mode functions (IMFs) of the waveform. Then, the Hilbert transform (HT) is applied to the IMFs to obtain the Hilbert spectrum of the waveform. As a result, the method is superiority of the processing of end effect of HHT to obtain the real frequency spectrum of signals.

Keywords: Neural network, back-propagation network, Hilbert-Huang transform

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Authors: P. S. Gomathi, B. Kalaavathi

Abstract:

The process in which the complementary information from multiple images is integrated to provide composite image that contains more information than the original input images is called image fusion. Medical image fusion provides useful information from multimodality medical images that provides additional information to the doctor for diagnosis of diseases in a better way. This paper represents the wavelet based medical image fusion algorithm on different multimodality medical images. In order to fuse the medical images, images are decomposed using Redundant Wavelet Transform (RWT). The high frequency coefficients are convolved with morphological operator followed by the maximum-selection (MS) rule. The low frequency coefficients are processed by MS rule. The reconstructed image is obtained by inverse RWT. The quantitative measures which includes Mean, Standard Deviation, Average Gradient, Spatial frequency, Edge based Similarity Measures are considered for evaluating the fused images. The performance of this proposed method is compared with Pixel averaging, PCA, and DWT fusion methods. When compared with conventional methods, the proposed framework provides better performance for analysis of multimodality medical images.

Keywords: Discrete Wavelet Transform (DWT), Image Fusion, Morphological Processing, Redundant Wavelet Transform (RWT).

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Authors: Shang-Lin Hsieh, Lung-Yao Hsu, I-Ju Tsai

Abstract:

This paper proposes a copyright protection scheme for color images using secret sharing and wavelet transform. The scheme contains two phases: the share image generation phase and the watermark retrieval phase. In the generation phase, the proposed scheme first converts the image into the YCbCr color space and creates a special sampling plane from the color space. Next, the scheme extracts the features from the sampling plane using the discrete wavelet transform. Then, the scheme employs the features and the watermark to generate a principal share image. In the retrieval phase, an expanded watermark is first reconstructed using the features of the suspect image and the principal share image. Next, the scheme reduces the additional noise to obtain the recovered watermark, which is then verified against the original watermark to examine the copyright. The experimental results show that the proposed scheme can resist several attacks such as JPEG compression, blurring, sharpening, noise addition, and cropping. The accuracy rates are all higher than 97%.

Keywords: Color image, copyright protection, discrete wavelet transform, secret sharing, watermarking.

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Authors: Ken-Lin Chang, Jun-Hong Lin, Shui-Tein Chen

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In this study, we used a two-stage process and potassium hydroxide (KOH) to transform waste biomass (rice straw) into activated carbon and then evaluated the adsorption capacity of the waste for removing carbofuran from an aqueous solution. Activated carbon was fast and effective for the removal of carbofuran because of its high surface area. The native and carbofuran-loaded adsorbents were characterized by elemental analysis. Different adsorption parameters, such as the initial carbofuran concentration, contact time, temperature and pH for carbofuran adsorption, were studied using a batch system. This study demonstrates that rice straw can be very effective in the adsorption of carbofuran from bodies of water.

Keywords: Rice straw, Carbofuran, Activated carbon

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Authors: Sunil Dehipawala, Aregama Sirisumana, P. Schneider, G. Tremberger Jr, D. Lieberman, Todd Holden T. Cheung

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The arsenic and iron environments in different growth stages have been studied with EXAFS and XANES using Brookhaven Synchrotron Light Source. Collard Greens plants were grown and tissue samples were harvested. The project studied the EXAFS and XANES of tissue samples using As and Fe K-edges. The Fe absorption and the Fourier transform bond length information were used as a control comparison. The Fourier transform of the XAFS data revealed the coexistence of As (III) and As (V) in the As bonding environment inside the studied plant tissue samples, although the soil only had As (III). The data suggests that Collard Greens has a novel pathway to handle arsenic absorption in soil.

Keywords: EXAFS, Fourier Transform, metalloproteins, XANES.

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Authors: Liu Dan, Wang Xue, Wang Guiqin, Qian Zhihong

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The burst noise is a kind of noises that are destructive and frequently found in semiconductor devices and ICs, yet detecting and removing the noise has proved challenging for IC designers or users. According to the properties of burst noise, a methodological approach is presented (proposed) in the paper, by which the burst noise can be analysed and detected in time domain. In this paper, principles and properties of burst noise are expounded first, Afterwards, feasibility (viable) of burst noise detection by means of wavelet transform in the time domain is corroborated in the paper, and the multi-resolution characters of Gaussian noise, burst noise and blurred burst noise are discussed in details by computer emulation. Furthermore, the practical method to decide parameters of wavelet transform is acquired through a great deal of experiment and data statistics. The methodology may yield an expectation in a wide variety of applications.

Keywords: Burst noise, detection, wavelet transform

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Authors: Michael Zimba

Abstract:

A duplicated image region may be subjected to a number of attacks such as noise addition, compression, reflection, rotation, and scaling with the intention of either merely mating it to its targeted neighborhood or preventing its detection. In this paper, we present an effective and robust method of detecting duplicated regions inclusive of those affected by the various attacks. In order to reduce the dimension of the image, the proposed algorithm firstly performs discrete wavelet transform, DWT, of a suspicious image. However, unlike most existing copy move image forgery (CMIF) detection algorithms operating in the DWT domain which extract only the low frequency subband of the DWT of the suspicious image thereby leaving valuable information in the other three subbands, the proposed algorithm simultaneously extracts features from all the four subbands. The extracted features are not only more accurate representation of image regions but also robust to additive noise, JPEG compression, and affine transformation. Furthermore, principal component analysis-eigenvalue decomposition, PCA-EVD, is applied to reduce the dimension of the features. The extracted features are then sorted using the more computationally efficient Radix Sort algorithm. Finally, same affine transformation selection, SATS, a duplication verification method, is applied to detect duplicated regions. The proposed algorithm is not only fast but also more robust to attacks compared to the related CMIF detection algorithms. The experimental results show high detection rates. 

Keywords: Affine Transformation, Discrete Wavelet Transform, Radix Sort, SATS.

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Authors: Khalid M. Aamir, Mohammad A. Maud

Abstract:

Power Spectral Density (PSD) computed by taking the Fourier transform of auto-correlation functions (Wiener-Khintchine Theorem) gives better result, in case of noisy data, as compared to the Periodogram approach. However, the computational complexity of Wiener-Khintchine approach is more than that of the Periodogram approach. For the computation of short time Fourier transform (STFT), this problem becomes even more prominent where computation of PSD is required after every shift in the window under analysis. In this paper, recursive version of the Wiener-Khintchine theorem has been derived by using the sliding DFT approach meant for computation of STFT. The computational complexity of the proposed recursive Wiener-Khintchine algorithm, for a window size of N, is O(N).

Keywords: Power Spectral Density (PSD), Wiener-KhintchineTheorem, Periodogram, Short Time Fourier Transform (STFT), TheSliding DFT.

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Authors: M.Ghazvini, S. A. Monadjemi, N. Movahhedinia, K. Jamshidi

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In this article, a method has been offered to classify normal and defective tiles using wavelet transform and artificial neural networks. The proposed algorithm calculates max and min medians as well as the standard deviation and average of detail images obtained from wavelet filters, then comes by feature vectors and attempts to classify the given tile using a Perceptron neural network with a single hidden layer. In this study along with the proposal of using median of optimum points as the basic feature and its comparison with the rest of the statistical features in the wavelet field, the relational advantages of Haar wavelet is investigated. This method has been experimented on a number of various tile designs and in average, it has been valid for over 90% of the cases. Amongst the other advantages, high speed and low calculating load are prominent.

Keywords: Defect detection, tile and ceramic quality inspection, wavelet transform, classification, neural networks, statistical features.

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Authors: Yu Bin, Zhang Yan

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The prediction of transmembrane helical segments (TMHs) in membrane proteins is an important field in the bioinformatics research. In this paper, a new method based on discrete wavelet transform (DWT) has been developed to predict the number and location of TMHs in membrane proteins. PDB coded as 1KQG was chosen as an example to describe the prediction of the number and location of TMHs in membrane proteins by using this method. To access the effect of the method, 80 proteins with known 3D-structure from Mptopo database are chosen at random as the test objects (including 325 TMHs), 308 of which can be predicted accurately, the average predicted accuracy is 96.3%. In addition, the above 80 membrane proteins are divided into 13 groups according to their function and type. In particular, the results of the prediction of TMHs of the 13 groups are satisfying.

Keywords: discrete wavelet transform, hydrophobicity, membrane protein, transmembrane helical segments

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Authors: B. I. Yun

Abstract:

A dual-reciprocity boundary element method is presented for the numerical solution of a class of axisymmetric elastodynamic problems. The domain integrals that arise in the integrodifferential formulation are converted to line integrals by using the dual-reciprocity method together suitably constructed interpolating functions. The second order time derivatives of the displacement in the governing partial differential equations are suppressed by using Laplace transformation. In the Laplace transform domain, the problem under consideration is eventually reduced to solving a system of linear algebraic equations. Once the linear algebraic equations are solved, the displacement and stress fields in the physical domain can be recovered by using a numerical technique for inverting Laplace transforms.

Keywords: Axisymmetric elasticity, boundary element method, dual-reciprocity method, Laplace transform.

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Authors: Moneeb Gohar, Seok Joo Koh, Tae-Won Um, Hyun-Woo Lee

Abstract:

This paper proposes a fast tree join scheme to provide seamless multicast handover in the mobile networks based on the Fast Mobile IPv6 (FMIPv6). In the existing FMIPv6-based multicast handover scheme, the bi-directional tunnelling or the remote subscription is employed with the packet forwarding from the previous access router (AR) to the new AR. In general, the remote subscription approach is preferred to the bi-directional tunnelling one, since in the remote subscription scheme we can exploit an optimized multicast path from a multicast source to many mobile receivers. However, in the remote subscription scheme, if the tree joining operation takes a long time, the amount of data packets to be forwarded and buffered for multicast handover will increase, and thus the corresponding buffer may overflow, which results in severe packet losses. In order to reduce these costs associated with packet forwarding and buffering, this paper proposes the fast join to multicast tree, in which the new AR will join the multicast tree as fast as possible, so that the new multicast data packets can also arrive at the new AR, by which the packet forwarding and buffering costs can be reduced. From numerical analysis, it is shown that the proposed scheme can give better performance than the existing FMIPv6-based multicast handover schemes in terms of the multicast packet delivery costs.

Keywords: Mobile Multicast, FMIPv6, Seamless Handover, Fast Tree Join.

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Authors: Zahra Yaghoubi, Nooshin Bigdeli, Karim Afshar

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This paper at first presents approximate analytical solutions for systems of fractional differential equations using the differential transform method. The application of differential transform method, developed for differential equations of integer order, is extended to derive approximate analytical solutions of systems of fractional differential equations. The solutions of our model equations are calculated in the form of convergent series with easily computable components. After that a drive-response synchronization method with linear output error feedback is presented for “generalized projective synchronization" for a class of fractional-order chaotic systems via a scalar transmitted signal. Genesio_Tesi and Duffing systems are used to illustrate the effectiveness of the proposed synchronization method.

Keywords: Generalized projective synchronization; Fractionalorder;Chaos; Caputo derivative; Differential transform method

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Authors: Ramesh K. Sunkaria

Abstract:

The linear methods of heart rate variability analysis such as non-parametric (e.g. fast Fourier transform analysis) and parametric methods (e.g. autoregressive modeling) has become an established non-invasive tool for marking the cardiac health, but their sensitivity and specificity were found to be lower than expected with positive predictive value <30%. This may be due to considering the RR-interval series as stationary and re-sampling them prior to their use for analysis, whereas actually it is not. This paper reviews the non-linear methods of HRV analysis such as correlation dimension, largest Lyupnov exponent, power law slope, fractal analysis, detrended fluctuation analysis, complexity measure etc. which are currently becoming popular as these uses the actual RR-interval series. These methods are expected to highly accurate cardiac health prognosis.

Keywords: chaos, nonlinear dynamics, sample entropy, approximate entropy, detrended fluctuation analysis.

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Authors: Md. Anwar Hossain Masud, Xiaodi Huang

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The massive proliferation of affordable computers, Internet broadband connectivity and rich education content has created a global phenomenon in which information and communication technology (ICT) is being used to transform education. Therefore, there is a need to redesign the educational system to meet the needs better. The advent of computers with sophisticated software has made it possible to solve many complex problems very fast and at a lower cost. This paper introduces the characteristics of the current E-Learning and then analyses the concept of cloud computing and describes the architecture of cloud computing platform by combining the features of E-Learning. The authors have tried to introduce cloud computing to e-learning, build an e-learning cloud, and make an active research and exploration for it from the following aspects: architecture, construction method and external interface with the model.

Keywords: Architecture, Cloud Computing, E-learning, Information Technology

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Authors: Samia Salah, M’hamed Hadj Sadok, Abderrezak Guessoum

Abstract:

In this paper, we propose a new modular approach called neuroglial consisting of two neural networks slow and fast which emulates a biological reality recently discovered. The implementation is based on complex multi-time scale systems; validation is performed on the model of the asynchronous machine. We applied the geometric approach based on the Gerschgorin circles for the decoupling of fast and slow variables, and the method of singular perturbations for the development of reductions models.

This new architecture allows for smaller networks with less complexity and better performance in terms of mean square error and convergence than the single network model.

Keywords: Gerschgorin’s Circles, Neuroglial Network, Multi time scales systems, Singular perturbation method.

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Authors: Hazem M. El-Bakry, Ahmed A. Mohammed

Abstract:

In this paper, an intelligent algorithm for optimal document archiving is presented. It is kown that electronic archives are very important for information system management. Minimizing the size of the stored data in electronic archive is a main issue to reduce the physical storage area. Here, the effect of different types of Arabic fonts on electronic archives size is discussed. Simulation results show that PDF is the best file format for storage of the Arabic documents in electronic archive. Furthermore, fast information detection in a given PDF file is introduced. Such approach uses fast neural networks (FNNs) implemented in the frequency domain. The operation of these networks relies on performing cross correlation in the frequency domain rather than spatial one. It is proved mathematically and practically that the number of computation steps required for the presented FNNs is less than that needed by conventional neural networks (CNNs). Simulation results using MATLAB confirm the theoretical computations.

Keywords: Information Storage and Retrieval, Electronic Archiving, Fast Information Detection, Cross Correlation, Frequency Domain.

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Authors: Juyoung Kim, Taegeun Park

Abstract:

In this paper, we propose a fully-utilized, block-based 2D DWT (discrete wavelet transform) architecture, which consists of four 1D DWT filters with two-channel QMF lattice structure. The proposed architecture requires about 2MN-3N registers to save the intermediate results for higher level decomposition, where M and N stand for the filter length and the row width of the image respectively. Furthermore, the proposed 2D DWT processes in horizontal and vertical directions simultaneously without an idle period, so that it computes the DWT for an N×N image in a period of N2(1-2-2J)/3. Compared to the existing approaches, the proposed architecture shows 100% of hardware utilization and high throughput rates. To mitigate the long critical path delay due to the cascaded lattices, we can apply the pipeline technique with four stages, while retaining 100% of hardware utilization. The proposed architecture can be applied in real-time video signal processing.

Keywords: discrete wavelet transform, VLSI architecture, QMF lattice filter, pipelining.

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Authors: K. Sakthivel, R. Nallusamy, C. Kavitha

Abstract:

The system is designed to show images which are related to the query image. Extracting color, texture, and shape features from an image plays a vital role in content-based image retrieval (CBIR). Initially RGB image is converted into HSV color space due to its perceptual uniformity. From the HSV image, Color features are extracted using block color histogram, texture features using Haar transform and shape feature using Fuzzy C-means Algorithm. Then, the characteristics of the global and local color histogram, texture features through co-occurrence matrix and Haar wavelet transform and shape are compared and analyzed for CBIR. Finally, the best method of each feature is fused during similarity measure to improve image retrieval effectiveness and accuracy.

Keywords: Color Histogram, Haar Wavelet Transform, Fuzzy C-means, Co-occurrence matrix; Similarity measure.

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Authors: Qiu Chen, Feifei Lee, Koji Kotani, Tadahiro Ohmi

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In this paper, we propose an efficient hierarchical DNA sequence search method to improve the search speed while the accuracy is being kept constant. For a given query DNA sequence, firstly, a fast local search method using histogram features is used as a filtering mechanism before scanning the sequences in the database. An overlapping processing is newly added to improve the robustness of the algorithm. A large number of DNA sequences with low similarity will be excluded for latter searching. The Smith-Waterman algorithm is then applied to each remainder sequences. Experimental results using GenBank sequence data show the proposed method combining histogram information and Smith-Waterman algorithm is more efficient for DNA sequence search.

Keywords: Fast search, DNA sequence, Histogram feature, Smith-Waterman algorithm, Local search

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Authors: G. Van Dijck, M. M. Van Hulle, M. Wevers

Abstract:

A genetic algorithm (GA) based feature subset selection algorithm is proposed in which the correlation structure of the features is exploited. The subset of features is validated according to the classification performance. Features derived from the continuous wavelet transform are potentially strongly correlated. GA-s that do not take the correlation structure of features into account are inefficient. The proposed algorithm forms clusters of correlated features and searches for a good candidate set of clusters. Secondly a search within the clusters is performed. Different simulations of the algorithm on a real-case data set with strong correlations between features show the increased classification performance. Comparison is performed with a standard GA without use of the correlation structure.

Keywords: Classification, genetic algorithm, hierarchicalagglomerative clustering, wavelet transform.

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Authors: Bahi brahim, El hassane Ibn Elhaj, Driss Aboutajdine

Abstract:

In this paper we propose a Multiple Description Image Coding(MDIC) scheme to generate two compressed and balanced rates descriptions in the wavelet domain (Daubechies biorthogonal (9, 7) wavelet) using pairwise correlating transform optimal and application method for Generalized Multiple Description Coding (GMDC) to image coding in the wavelet domain. The GMDC produces statistically correlated streams such that lost streams can be estimated from the received data. Our performance test shown that the proposed method gives more improvement and good quality of the reconstructed image when the wavelet coefficients are normalized by Gaussian Scale Mixture (GSM) model then the Gaussian one ,.

Keywords: Multiple description coding (MDC), gaussian scale mixture (GSM) model, joint source-channel coding, pairwise correlating transform, GMDCT.

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Authors: B. X. Tchomeni, A. A. Alugongo, L. M. Masu

Abstract:

An analytical 4-DOF nonlinear model of a de Laval rotor-stator system based on Energy Principles has been used theoretically and experimentally to investigate fault symptoms in a rotating system. The faults, namely rotor-stator-rub, crack and unbalance are modeled as excitations on the rotor shaft. Mayes steering function is used to simulate the breathing behaviour of the crack. The fault analysis technique is based on waveform signal, orbits and Fast Fourier Transform (FFT) derived from simulated and real measured signals. Simulated and experimental results manifest considerable mutual resemblance of elliptic-shaped orbits and FFT for a same range of test data.

Keywords: A breathing crack, fault, FFT, nonlinear, orbit, rotorstator rub, vibration analysis.

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Authors: J. Luebkemann, P. Nyhuis

Abstract:

Nowadays companies are facing an increasing turbulent environment. It is more and more important to react fast on changes to stay competitive. But not only the technology has to be adaptable; also the frame conditions for the production have to adapt as fast as the other elements of a manufacturing company. Therefore, the Institute of Production Systems and Logistics of the Leibniz University of Hanover has implemented a research project to describe and develop changeable organizational structures. The results of the analysis, which design principles can be used to evolve an organizational structure of a factory regarding their changeability will be presented in this paper.

Keywords: Changeability, factory, organization.

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Authors: Mamta Garg

Abstract:

While compressing text files is useful, compressing still image files is almost a necessity. A typical image takes up much more storage than a typical text message and without compression images would be extremely clumsy to store and distribute. The amount of information required to store pictures on modern computers is quite large in relation to the amount of bandwidth commonly available to transmit them over the Internet and applications. Image compression addresses the problem of reducing the amount of data required to represent a digital image. Performance of any image compression method can be evaluated by measuring the root-mean-square-error & peak signal to noise ratio. The method of image compression that will be analyzed in this paper is based on the lossy JPEG image compression technique, the most popular compression technique for color images. JPEG compression is able to greatly reduce file size with minimal image degradation by throwing away the least “important" information. In JPEG, both color components are downsampled simultaneously, but in this paper we will compare the results when the compression is done by downsampling the single chroma part. In this paper we will demonstrate more compression ratio is achieved when the chrominance blue is downsampled as compared to downsampling the chrominance red in JPEG compression. But the peak signal to noise ratio is more when the chrominance red is downsampled as compared to downsampling the chrominance blue in JPEG compression. In particular we will use the hats.jpg as a demonstration of JPEG compression using low pass filter and demonstrate that the image is compressed with barely any visual differences with both methods.

Keywords: JPEG, Discrete Cosine Transform, Quantization, Color Space Conversion, Image Compression, Peak Signal to Noise Ratio & Compression Ratio.

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Authors: Varun Setia, Vinod Kumar

Abstract:

In present paper we proposed a simple and effective method to compress an image. Here we found success in size reduction of an image without much compromising with it-s quality. Here we used Haar Wavelet Transform to transform our original image and after quantization and thresholding of DWT coefficients Run length coding and Huffman coding schemes have been used to encode the image. DWT is base for quite populate JPEG 2000 technique.

Keywords: Lossy compression, DWT, quantization, Run length coding, Huffman coding, JPEG2000.

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Authors: Peyman Shadman Heidari, Mohammad Khorasani

Abstract:

The principal purpose of this article is to present a new method based on Adaptive Neural Network Fuzzy Inference System (ANFIS) to generate additional artificial earthquake accelerograms from presented data, which are compatible with specified response spectra. The proposed method uses the learning abilities of ANFIS to develop the knowledge of the inverse mapping from response spectrum to earthquake records. In addition, wavelet packet transform is used to decompose specified earthquake records and then ANFISs are trained to relate the response spectrum of records to their wavelet packet coefficients. Finally, an interpretive example is presented which uses an ensemble of recorded accelerograms to demonstrate the effectiveness of the proposed method.

Keywords: Adaptive Neural Network Fuzzy Inference System, Wavelet Packet Transform, Response Spectrum.

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Authors: V. Weinzettl, M. Imrisek, J. Havlicek, J. Mlynar, D. Naydenkova, P. Hacek, M. Hron, F. Janky, D. Sarychev, M. Berta, A. Bencze, T. Szabolics

Abstract:

Semiconductor detector arrays are widely used in high-temperature plasma diagnostics. They have a fast response, which allows observation of many processes and instabilities in tokamaks. In this paper, there are reviewed several diagnostics based on semiconductor arrays as cameras, AXUV photodiodes (referred often as fast “bolometers") and detectors of both soft X-rays and visible light installed on the COMPASS tokamak recently. Fresh results from both spring and summer campaigns in 2012 are introduced. Examples of the utilization of the detectors are shown on the plasma shape determination, fast calculation of the radiation center, two-dimensional plasma radiation tomography in different spectral ranges, observation of impurity inflow, and also on investigation of MHD activity in the COMPASS tokamak discharges.

Keywords: Bolometry, plasma diagnostics, soft X-rays, tokamak.

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Authors: Slimane Ouhmad, Abdellah Halimi

Abstract:

In this work, neural networks methods MLP type were applied to a database from an array of six sensors for the detection of three toxic gases. The choice of the number of hidden layers and the weight values are influential on the convergence of the learning algorithm. We proposed, in this article, a mathematical formula to determine the optimal number of hidden layers and good weight values based on the method of back propagation of errors. The results of this modeling have improved discrimination of these gases and optimized the computation time. The model presented here has proven to be an effective application for the fast identification of toxic gases.

Keywords: Back-propagation, Computing time, Fast identification, MLP neural network, Number of neurons in the hidden layer.

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