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    Estimation of flow stress behavior of AA5083 using artificial neural networks with regard to dynamic strain ageing effect

    , Article Journal of Materials Processing Technology ; Volume 196, Issue 1-3 , 2008 , Pages 115-119 ; 09240136 (ISSN) Sheikh, H ; Serajzadeh, S ; Sharif University of Technology
    In this work, neural networks are used for estimation of flow stress of AA5083 with regard to dynamic strain ageing that occurs in certain deformation conditions and varies flow stress behavior of the metal being deformed. The input variables are selected to be strain rate, temperature and strain and the output value is the flow stress. In the first stage, the appearance and terminal of dynamic strain aging are determined with the aid of tensile testing at various temperatures and strain rates and subsequently for the serrated flow and the smooth yielding domains different neural networks are constructed based on the achieved results. While a feed-forward backpropagation algorithm is... 

    A method for noise reduction in active-rc circuits

    , Article IEEE Transactions on Circuits and Systems II: Express Briefs ; Volume 58, Issue 12 , 2011 , Pages 906-910 ; 15497747 (ISSN) Gharibdoust, K ; Bakhtiar, M. S ; Sharif University of Technology
    A method for noise reduction in active-$RC$ circuits is introduced. It is shown that the output noise in an active-$RC$ circuit can be considerably reduced, without disturbing the circuit transfer function by inserting appropriate passive or active components in the circuit. The inserted components introduce new signal paths in the circuit for noise reduction while the original circuit transfer function is kept unchanged. The procedure to define the proper paths in the circuit and their transfer functions is given. The effectiveness of the presented method is demonstrated using a second-order active-RC filter fabricated in a 0.18-$ {m}$ CMOS technology  

    Novel frequency synthesizer for spur level reduction

    , Article 27th Iranian Conference on Electrical Engineering, ICEE 2019, 30 April 2019 through 2 May 2019 ; 2019 , Pages 76-81 ; 9781728115085 (ISBN) Choopani, A ; Ghajari, S ; Safarian, A ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2019
    A novel frequency synthesizer architecture for reducing spur level is presented. By using a feedforward path a new zero in the transfer function is generated which enables us to increase the capacitor tied to the control voltage line and thus reducing spur level. A fast settling technique is also used to compensate the effect of spur reduction technique on settling time. Different blocks of frequency synthesizer are implemented in MATLAB/Simulink. Simulations show 13 dB improvement in reference spur level compared to conventional architecture for a 2.4 GHz frequency synthesizer  

    An S-Band CMOS 6-Bit vector-sum phase shifter with low RMS phase error using frequency-to-voltage converter feedforward loop

    , Article Journal of Circuits, Systems and Computers ; Volume 29, Issue 3 , 2020 Nobakht Sarkezeh, M ; Safarian, A ; Sharif University of Technology
    World Scientific Publishing Co. Pte Ltd  2020
    In this paper, a wideband full-360o phase shifter with 6 bits of accuracy has been designed and simulated with minimal root mean square (RMS) phase error. The proposed phase shifter deployed a feed forward path including a frequency-to-voltage converter (FVC) to minimize the mismatch in quadrature generation to eventually reduce the RMS phase error for S-band (2-4GHz) applications. The designed phase shifter in 180nm CMOS technology achieves an RMS phase error in the range of 0.607-1.18? with -50dBm input signal over 2-4GHz frequency band. With lower input signal of -75dBm, the RMS phase error is 0.621-1.34? for 2-4GHz input frequency. The proposed phase shifter shows an RMS amplitude error... 

    Optimal Control of Batch Cooling Crystallizers Using Inversion Approach

    , M.Sc. Thesis Sharif University of Technology Amini, Younes (Author) ; Pishvaie, Mahmoud Reza (Supervisor)
    In batch cooling crystallization, the crucial control problem is to design a temperature trajectory which produces a desired crystal size distribution. Here, a completely different solution is presented. Designing model-based controller for crystallizer has two steps; first step is determining optimal temperature trajectory which is some kind of feedforward control, second step is adding feedback controller (with manipulated variable of jacket temperature or cooling flow) to track the set-point (determined in first step) and rejecting possible disturbances. Traditionally, determining optimal temperature of crystallizer is done by using calculus of variations of distributed system. In this... 

    Clad height control in laser solid freeform fabrication using a feedforward PID controller

    , Article International Journal of Advanced Manufacturing Technology ; Volume 35, Issue 3-4 , 2007 , Pages 280-292 ; 02683768 (ISSN) Fathi, A ; Khajepour, A ; Toyserkani, E ; Durali, M ; Sharif University of Technology
    In this paper, a feedforward proportional-integral-derivative (PID) controller is developed to effectively control the clad height in laser solid freeform fabrication (LSFF). The scanning velocity is selected as the input control variable and the clad height is chosen as the output. A novel knowledge-based Hammerstein model, including a linear dynamic and a nonlinear memoryless block, is developed, and its parameters are identified offline using experimental data. The architecture of the controller consists of a PID and a feedforward module, which is the inverse of the identified model. The advantage of adding a feedforward path to the PID controller is evaluated experimentally, in which the... 

    Static and dynamic neural networks for simulation and optimization of cogeneration systems

    , Article 2006 ASME 51st Turbo Expo, Barcelona, 6 May 2006 through 11 May 2006 ; Volume 4 , 2006 , Pages 615-623 ; 0791842398 (ISBN); 9780791842393 (ISBN) Zomorodian, R ; Khaledi, H ; Ghofrani, M. B ; The International Gas Turbine Institute ; Sharif University of Technology
    In this paper, the application of neural networks for simulation and optimization of the cogeneration systems has been presented. CGAM problem, a benchmark in cogeneration systems, is chosen as a case study. Thermodynamic model includes precise modeling of the whole plant. For simulation of the steady sate behavior, the static neural network is applied. Then using dynamic neural network, plant is optimized thermodynamically. Multi layer feed forward neural networks is chosen as static net and recurrent neural networks as dynamic net. The steady state behavior of CGAM problem is simulated by MFNN. Subsequently, it is optimized by dynamic net. Results of static net have excellence agreement... 

    A neural network aided adaptive second-order gaussian filter for tracking maneuvering targets

    , Article ICTAI 2005: 17th IEEE International Conference on Tools with Artificial Intelligence, ICTAI'05, Hong Kong, 14 November 2005 through 16 November 2005 ; Volume 2005 , 2005 , Pages 439-446 ; 10823409 (ISSN); 0769524885 (ISBN); 9780769524887 (ISBN) Sadati, N ; Langary, D ; Sharif University of Technology
    The adaptive capability of filters is known to be increased by incorporating a neural network into the filtering procedure. In this paper, an adaptive algorithm for tracking maneuvering targets based on neural networks is proposed. This algorithm is implemented with two filters based on the current statistical model and a multilayer feedforward neural network. The two filters track the same maneuvering target in parallel and the neural network automatically considers all the state information of the two filters and adaptively adjusts the process variance of one of them to achieve better performance in different target maneuver tracking. Simulations results show that the proposed adaptive... 

    Blood Glucose Control in Human Body Using Model-Based Controllers

    , M.Sc. Thesis Sharif University of Technology Abedini Najafabadi, Hamed (Author) ; Shahrokhi, Mohammad (Supervisor)
    Continous blood glucose control has great importance for type 1 dyabetic patients. In this thesis, several types of controllers including: PI controller, model predictive controller base on state space model, linear model predictive controller base of linear input-output model and non-linear model predictive controller base of Hammerstein model have been used to regulate blood glucose of patients with type 1 diabetes. These models are identified using least squars method. Performance of these controllers is tested and the best one is introduced. For rejecting meal disturbances, a feedforward controller has been designed. Combination of feedback and feedforward controller would properly... 

    Dynamical Modeling and Control of an XY Nano-Positioner with Flexural Mechanism

    , M.Sc. Thesis Sharif University of Technology Heravi, Mohammad (Author) ; Salarieh, Hasan (Supervisor) ; Nejat Pishkenari, Hossein (Supervisor)
    Nowadays, nano-positioners play an important role in advanced technologies, such as atomic force microscopy, genetic manipulation, nano-metrology, nano-fabrication, semi-conductors and etc.In this paper, a dynamical model has been derived for a nano-positioner. This nanopositioner was designed and fabricated in Sharif university of technology. In this paper the mentioned mechanism has been considered as a planar mechanism. First, a finite element model has been developed in Comsol multi-physics software. This model was used as the reference model in the next steps. Afterward, a 10 degrees of freedom model was proposed to estimate the Comsol model. The mass, stiffness, as well as damping... 

    Model Predictive Control in the Presence of Model Uncertainty and Communication Imperfections: Application in Automated Irrigation Channels

    , M.Sc. Thesis Sharif University of Technology Rahmati Zadeh, Bahar (Author) ; Farhadi, Alireza (Supervisor)
    In this thesis, at first upstream transient error propagation and amplification phenomenon is introduced. Then, the previous methods to attenuate this phenomenon are presented. To overcome this drawback, a new method that is based on feed-forward and off-take disturbance estimation and lost data reconstruction in wireless communication is presented. In this thesis, an estimation of unknown off-take disturbance at the present time is approximated or in fact predicted using the last data. Also, in the presented method, the lost data is reconstructed using two different methods. At the end, the satisfactory performance of the proposed control method is illustrated by many computer simulations  

    Automatic Recognition of Quranic Maqams Using Machine Learning

    , M.Sc. Thesis Sharif University of Technology Khodabandeh, Mohammad Javad (Author) ; Sameti, Hossein (Supervisor) ; Bahrani, Mohammad (Supervisor)
    Automatic recognition of musical Maqams has been one of the challenging problems in Music Information Retrieval. Despite the increasing amount of related research in recent years, we are still far away from building related real-life applications. Nevertheless, a very small portion of these research is dedicated to automatic recognition of Maqams in recitation of the Holy Quran. In this thesis, as a first attempt, we have used machine learning methods to classify six Maqam families which are commonly used in Quran recitation. Also, due to the lack of pre-exisiting datasets, we have annotated approximately 1325 minutes of Tadwir recitation from two prominent Egyptian reciters, i.e., Muhammad... 

    The prediction of the density of undersaturated crude oil using multilayer feed-forward back-propagation perceptron

    , Article Petroleum Science and Technology ; Volume 30, Issue 1 , 2011 , Pages 89-99 ; 10916466 (ISSN) Rostami, H ; Shahkarami, A ; Azin, R ; Sharif University of Technology
    Crude oil density is an important thermodynamic property in simulation processes and design of equipment. Using laboratory methods to measure crude oil density is costly and time consuming; thus, predicting the density of crude oil using modeling is cost-effective. In this article, we develop a neural network-based model to predict the density of undersaturated crude oil. We compare our results with previous works and show that our method outperforms them  

    Multiple sclerosis diagnosis based on analysis of subbands of 2-D wavelet transform applied on MR-images

    , Article 2007 IEEE/ACS International Conference on Computer Systems and Applications, AICCSA 2007, Amman, 13 May 2007 through 16 May 2007 ; 2007 , Pages 717-721 ; 1424410312 (ISBN); 9781424410316 (ISBN) Torabi, M ; Moradzadeh, H ; Vaziri, R ; Dehestani Ardekani, R ; Fatemizadeh, E ; Sharif University of Technology
    In this study, we have proposed a novel approach to investigate the features of four subbands of 2-D wavelet transform in magnetic resonance images (MRIs) for normal and abnormal brains which defected by Multiple Sclerosis (MS). Concurrently, another method extracts different kinds of features in spatial domain. Totally, 116 features have been extracted. Before applying the algorithm, we have to use a registration method because of variety in size of brain images. All extracted features have been passed over the Principal Component Analysis (PCA) and have been pushed to an Artificial Neural Network (ANN) that is a feed-forward type. According to changing in position of defected parts of... 

    Voice conversion using nonlinear principal component analysis

    , Article 2007 IEEE Symposium on Computational Intelligence in Image and Signal Processing, CIISP 2007, Honolulu, HI, 1 April 2007 through 5 April 2007 ; 2007 , Pages 336-339 ; 1424407079 (ISBN); 9781424407071 (ISBN) Makki, B ; Seyed salehi, S. A ; Sadati, N ; Noori Hosseini, M ; Sharif University of Technology
    In the last decades, much attention has been paid to the design of multi-speaker voice conversion. In this work, a new method for voice conversion (VC) using nonlinear principal component analysis (NLPCA) is presented. The principal components are extracted and transformed by a feed-forward neural network which is trained by combination of Genetic Algorithm (GA) and Back-Propagation (BP). Common pre- and post-processing approaches are applied to increase the quality of the synthesized speech. The results indicate that the proposed method can be considered as a step towards multi-speaker Voice conversion. © 2007 IEEE  

    Optimal feedback-adaptive feedforward controller for vibration suppression of a cantilever beam using piezo-actuators

    , Article 8th Biennial ASME Conference on Engineering Systems Design and Analysis, ESDA2006, Torino, 4 July 2006 through 7 July 2006 ; Volume 2006 , 2006 ; 0791837793 (ISBN); 9780791837795 (ISBN) Kazemi, O ; Sayyaadi, H ; Behzad, M ; Sharif University of Technology
    American Society of Mechanical Engineers  2006
    In this paper the combined optimal feedback-adaptive feedforward controller proposed to attain better performance of active vibration suppression of flexible structures subjected to different type of disturbances. The structure considered here is a cantilever beam actuated with a PZT patch actuator. The proposed controller consists of two individual parts, a filtered-x controller as a feedforward part and an optimal linear controller as a feedback part. Recursive Least Square algorithm (RLS) is used for the adaptive filtering scheme in Filtered-x adaptive feedforward controller. LQG optimal controller is also used in the feedback part of the controller. This research investigates the... 

    Motion blur identification in noisy images using feed-forward back propagation neural network

    , Article International Workshop on Intelligent Computing in Pattern Analysis/Synthesis, IWICPAS 2006, Xi'an, 26 August 2006 through 27 August 2006 ; Volume 4153 LNCS , 2006 , Pages 369-376 ; 03029743 (ISSN); 354037597X (ISBN); 9783540375975 (ISBN) Ebrahimi Moghaddam, M ; Jamzad, M ; Mahini, H. R ; Sharif University of Technology
    Springer Verlag  2006
    Blur identification is one important part of image restoration process. Linear motion blur is one of the most common degradation functions that corrupts images. Since 1976, many researchers tried to estimate motion blur parameters and this problem is solved in noise free images but in noisy images improvement can be done when image SNR is low. In this paper we have proposed a method to estimate motion blur parameters such as direction and length using Radon transform and Feed-Forward back propagation neural network for noisy images. To design the desired neural network, we used Weierstrass approximation theorem and Steifel reference Sets. The experimental results showed algorithm precision... 

    Automatic detection of epileptic seizure using time-frequency distributions

    , Article IET 3rd International Conference MEDSIP 2006: Advances in Medical, Signal and Information Processing, Glasgow, 17 July 2006 through 19 July 2006 ; Issue 520 , 2006 , Pages 29- ; 0863416586 (ISBN); 9780863416583 (ISBN) Mohseni, H. R ; Maghsoudi, A ; Kadbi, M. H ; Hashemi, J ; Ashourvan, A ; Sharif University of Technology
    The aim of this work is to introduce a new method based on time frequency distribution for classifying the EEG signals. Some parameters are extracted using time-frequency distribution as inputs to a feed-forward backpropagation neural networks (FBNN). The proposed method had better results with 98.25% accuracy compared to previously studied methods such as wavelet transform, entropy, logistic regression and Lyapunov exponent  

    Vibration of beams with unconventional boundary conditions using artificial neural network

    , Article DETC2005: ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Long Beach, CA, 24 September 2005 through 28 September 2005 ; Volume 1 A , 2005 , Pages 159-165 ; 0791847381 (ISBN); 9780791847381 (ISBN) Hassanpour Asl, P ; Esmailzadeh, E ; Mehdigholi, H ; Sharif University of Technology
    American Society of Mechanical Engineers  2005
    The vibration of a simply-supported beam with rotary springs at either ends is studied. The governing equations of motion are investigated considering the nonlinear effect of stretching. These equations are made non-dimensional and solved to the first-order approximation using the two known methods, namely, the multiple scales and the mode summation. The first five natural frequencies of the beam for different pairs of the boundary condition parameters are evaluated. A multilayer feed-forward back-propagation artificial neural network is trained using these natural frequencies. The artificial neural network used in this study shows high degree of accuracy for the natural frequency of the... 

    Adaptive nonlinear observer design using feedforward neural networks

    , Article Scientia Iranica ; Volume 12, Issue 2 , 2005 , Pages 141-150 ; 10263098 (ISSN) Dehghan Nayeri, M. R ; Alasty, A ; Sharif University of Technology
    Sharif University of Technology  2005
    This paper concerns the design of a neural state observer for nonlinear dynamic systems with noisy measurement channels and in the presence of small model errors. The proposed observer consists of three feedforward neural parts, two of which are MLP universal approximators, which are being trained off-line and the last one being a Linearly Parameterized Neural Network (LPNN), which is being updated on-line. The off-line trained parts are able to generate state estimations instantly and almost accurately, if there are not catastrophic errors in the mathematical model used. The contribution of the on-line adapting part is to compensate the remainder estimation error due to uncertain parameters...