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A General Method for Noise Reduction in Active Filters
, M.Sc. Thesis Sharif University of Technology ; Sharif Bakhtiar, Mehrdad (Supervisor)
Abstract
Degradation of signal to noise ratio (SNR) in today's low voltage circuits has been a challenging problem for analogue circuit designing. This problem is produced due to supply voltage reduction and noise level consistency in today's analogue circuits. Great efforts have been done in literatures for noise reduction in some analogue circuits, like low noise amplifiers, but there is no general method for noise reduction in active filters and introduction of a general method for noise reduction in active filters which are in vast usage in all analogue circuits, has always been demanded by circuit designers. In this project, a general method for noise reduction in active RC filters is introduced...
Optimal Control of Batch Cooling Crystallizers Using Inversion Approach
, M.Sc. Thesis Sharif University of Technology ; Pishvaie, Mahmoud Reza (Supervisor)
Abstract
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...
Blood Glucose Control in Human Body Using Model-Based Controllers
,
M.Sc. Thesis
Sharif University of Technology
;
Shahrokhi, Mohammad
(Supervisor)
Abstract
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 ; Salarieh, Hasan (Supervisor) ; Nejat Pishkenari, Hossein (Supervisor)
Abstract
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 ; Farhadi, Alireza (Supervisor)
Abstract
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
Leakage Cancellation from Transmitter to Receiver
, M.Sc. Thesis Sharif University of Technology ; Atarodi, Mojtaba (Supervisor) ; Safarian, Amin Ghasem (Supervisor)
Abstract
The wideband code-division multiple access (WCDMA) system has been widely used for the third-generation wireless communication system. It uses Frequency division duplexing for two-way communication by a transceiver. Although a duplexer will significantly suppress the TX leakage signal (50dB-60dB), a residual attenuated signal still remains at the receiver input and act as a strong blocker which reduces the sensitivity of the receiver. For reducing the effect of the TX leakage on the RX performance, a band pass RF SAW filter is typically inserted between the LNA and the mixer to reject the TX leakage. However, this filter increases the system cost and size. This encouraged us to propose a novel...
On the Use of Artificial Neural Networks in Automatic Speech Recognition
, M.Sc. Thesis Sharif University of Technology ; Ghorshi, Mohammad Ali (Supervisor) ; Khayyat, Amir Ali Akbar (Supervisor)
Abstract
In this thesis, the Artificial Neural Networks (ANN) will be used in Automatic Speech Recognition (ASR) instead of Hidden Markov Models (HMM). Hidden Markov Model is one of the most dominant Bayesian network technologies and is the most successful model in current ASR systems. However, excessive training time is a major issue in speech recognition based on Hidden Markov Model (HMM). This thesis presents an Artificial Neural Network language model for human speech by mapping the spectral features of speech namely the formants, cepstrum (Mel-Frequency Cepstral Coefficients (MFCCs)) and Power Spectral Density (PSD) as features of samples of specific words into a discrete vector space. The...
Investigation on Application of Vibration and Sound Signals for Tool Condition Monitoring
, M.Sc. Thesis Sharif University of Technology ; Behzad, Mehdi (Supervisor) ; Akbari, Javad (Supervisor)
Abstract
Tool Condition Monitoring (TCM) is a vital demand of advanced manufacturing in order to develop automated unmanned production. Tool condition has an essential influence on machined surface quality and dimension of manufactured parts. Continuing machining operation with a worn or damaged tool will result in damages to workpiece and even the machine tool itself. This problem becomes more important in supplementary machining processes like drilling in which the workpiece is usually at the final stages of production and any damage to workpiece at this stage is irreparable and results in high production losses. In this thesis, sound and vibrations signals are analyzed for drill wear detection....
Automatic Recognition of Quranic Maqams Using Machine Learning
, M.Sc. Thesis Sharif University of Technology ; Sameti, Hossein (Supervisor) ; Bahrani, Mohammad (Supervisor)
Abstract
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...
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 ; Safarian, A ; Sharif University of Technology
World Scientific Publishing Co. Pte Ltd
2020
Abstract
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...
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) ; Jamzad, M ; Mahini, H. R ; Sharif University of Technology
Springer Verlag
2006
Abstract
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...
Adaptive attitude and position control of an insect-like flapping wing air vehicle
, Article Nonlinear Dynamics ; Volume 85, Issue 1 , 2016 , Pages 47-66 ; 0924090X (ISSN) ; Taymourtash, N ; Sharif University of Technology
Springer Netherlands
Abstract
This study describes an adaptive sliding mode technique for attitude and position control of a rigid body insect-like flapping wing model in the presence of uncertainties. For this purpose, a six-degrees-of-freedom nonlinear and time-varying dynamic model of a typical hummingbird is considered for simulation studies. Based on the quasi-steady assumptions, three major aerodynamic loads including delayed stall, rotational lift and added mass are presented and analyzed, respectively. Using the averaging theory, a time-varying system is then transformed into the time-invariant system to design the adaptive controller. The controller is designed so that the closed-loop system will follow any...
Extending concepts of mapping of human brain to artificial intelligence and neural networks
, Article Scientia Iranica ; Volume 28, Issue 3 D , 2021 , Pages 1529-1534 ; 10263098 (ISSN) ; Sharif University of Technology
Sharif University of Technology
2021
Abstract
This paper introduces the concept of mapping of Artificially Intelligent (AI) computational systems. The concept of homunculus from human neurophysiology is extended to AI systems. It is assumed that an AI system behaves similarly to a mini-column or ganglion in the natural animal brain that comprises a layer of afferent (input) neurons, a number of interconnecting processing cells, and a layer of efferent (output) neurons or organs. The objective of the present study was to identify the correlation between the stimulus to each afferent neuron and the corresponding response from each efferent organ when the intelligent system is subjected to certain stimuli. To clarify the general concept, a...
Adaptive nonlinear observer design using feedforward neural networks
, Article Scientia Iranica ; Volume 12, Issue 2 , 2005 , Pages 141-150 ; 10263098 (ISSN) ; Alasty, A ; Sharif University of Technology
Sharif University of Technology
2005
Abstract
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...
Model predictive control of blood sugar in patients with type-1 diabetes
, Article Optimal Control Applications and Methods ; Volume 37, Issue 4 , 2016 , Pages 559-573 ; 01432087 (ISSN) ; Shahrokhi, M ; Sharif University of Technology
John Wiley and Sons Ltd
Abstract
In this article, two adaptive model predictive controllers (AMPC) are applied to regulate the blood glucose in type 1 diabetic patients. The first controller is constructed based on a linear model, while the second one is designed by using a nonlinear Hammerstein model. The adaptive version of these control schemes is considered to make them more robust against model mismatches and external disturbances. The least squares method with forgetting factor is used to update the model parameters. For simulation study, two well-known mathematical models namely, Puckett and Hovorka which describe the dynamical behavior of patient's body have been selected. The performances and robustness of the...
Bounds on the approximation power of feed forward neural networks
, Article 35th International Conference on Machine Learning, ICML 2018, 10 July 2018 through 15 July 2018 ; Volume 8 , 2018 , Pages 5531-5539 ; 9781510867963 (ISBN) ; Tchamkerten, A ; Isvand Yousefi, M ; Sharif University of Technology
International Machine Learning Society (IMLS)
2018
Abstract
The approximation power of general feedforward neural networks with piecewise linear activation functions is investigated. First, lower bounds on the size of a network are established in terms of the approximation error and network depth and width. These bounds improve upon state- of-the-art bounds for certain classes of functions, such as strongly convex functions. Second, an upper bound is established on the difference of two neural networks with identical weights but different activation functions. © The Author(s) 2018
A novel method for segmentation of leukocyte nuclei based on color transformation
, Article 26th National and 4th International Iranian Conference on Biomedical Engineering, ICBME 2019, 27 November 2019 through 28 November 2019 ; 2019 , Pages 213-217 ; 9781728156637 (ISBN) ; Maheri, J ; Behroozi, H ; Kolahdoozi, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2019
Abstract
Acute lymphoblastic leukemia is one of the most common hematologic malignancies among children, caused by uncontrolled growth of leukocytes. Since the main hallmarks of the disease is not specific, a considerable number of patients have been being misdiagnosed. Early diagnosis of the disease is usually made by morphological investigation of leukocytes under microscope. In light of the facts that decrease in cytoplasm-to-nucleus ratio is one of the main indicators of cancerous cells, and an accurate segmentation phase will lead to extraction of representative features, segmentation step is acknowledged as being crucial in design of a computer aided diagnosis (CAD). Previous researches have...
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) ; Ghajari, S ; Safarian, A ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2019
Abstract
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 Extremely low ripple high voltage power supply for pulsed current applications
, Article IEEE Transactions on Power Electronics ; Volume 35, Issue 8 , 2020 , Pages 7991-8001 ; Mohsenzade, S ; Hadizade, A ; Kaboli, S ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2020
Abstract
This article describes the development of an 18 kV, 30 kW power supply for a pulsed current load with the maximum current of 20 A and a di/dt equal to 100 A/μs. The achieved output ripple is less than 0.01%. In such a high level of precision, the most important issues are considerable difference between the instantaneous and average output powers, as well as insufficient reaction speed of the converter to the fast load change. Very low level of the voltage feedback and its sensitivity to the noise. The first issue necessitates a notable overdesign of the converter switches if the output voltage precision is dedicated to the converter. The second issue raises the problems relevant to...
Neural control of a fully actuated biped robot
, Article IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics, Paris, 6 November 2006 through 10 November 2006 ; 2006 , Pages 3104-3109 ; 1424401364 (ISBN); 9781424401369 (ISBN) ; Hamed, K. A ; Sharif University of Technology
IEEE Computer Society
2006
Abstract
According to the fact that humans and animals show marvelous abilities in walking on irregular terrain, there is a strong need for adaptive algorithms in walking of biped robots to behave like them. Since the stance leg can easily rise from the ground and it can easily rotate about the toe or the heel, the problem of controlling the biped robots is difficult. In this paper, according to the adaptive locomotion patterns of animals, coordination and control of body links have been done with Central Pattern Generator (CPG) in spinal cord and feedback network from musculoskeletal system. A one layer feedforward neural network that its inputs are the scaled joint variables and the touch sensors...