Paper Title, Authors, Abstract (Issue 1, Volume 3, 2009)

Pages

Muli-Threshold Low Power Shift Register
Sameh Andrawes, Leila.Koushaeian, Ronny Veljanovski

Abstract: Low power design is a very important topic nowadays because of the battery life time especially for the portable embedded system, where the deep sub-micron technology makes the leakage current is the dominant current which was ignored in the past. Long battery life time can be obtained by minimising the power consumption. There are different techniques to do that while the most effective one is the low voltage level. We present the design and implementation of a low power Complementary Metal Oxide Semiconductor (CMOS) ten-bit shift register by using negative latch D Flip-Flop (DFF) in the sub-threshold region with high speed in the active mode and low power consumption during the sleep mode using Multi-threshold Complementary Metal Oxide Semiconductor (MTCMOS) technique. The circuit was implemented in 90 nm from STM CMOS technology, with oxide thickness of 16A0, 250 mV power supply, 5 MHz clock frequency with 10 % activity, average power consumption is 6.43 nW and power delay product (PDP) is 24.43 aJ. The shift register has been designed and simulated by using Cadence tools.
 

Condition Monitoring Methods, Failure Identification and Analysis for Induction Machines
Neelam Mehala, Ratna Dahiya

Abstract: Induction motors are a critical component of many industrial processes and are frequently integrated in commercially available equipment and industrial processes. The studies of induction motor behavior during abnormal conditions, and the possibility to diagnose different types of faults have been a challenging topic for many electrical machine researchers. The Motor Current Signature Analysis (MCSA) is considered the most popular fault detection method now a day because it can easily detect the common machine fault such as turn to turn short ckt, cracked /broken rotor bars, bearing deterioration etc. This paper presents theory and some experimental results of Motor current signature analysis. The MCSA uses the current spectrum of the machine for locating characteristic fault frequencies. The spectrum is obtained using a Fast Fourier Transformation (FFT) that is performed on the signal under analysis. The fault frequencies that occur in the motor current spectra are unique for different motor faults. However this method does not always achieve good results with non-constant load torque. Therefore, different signal processing methods, such as Short-time Fourier Transform (STFT) and Wavelet transforms techniques are also proposed and compared in this paper.
 

Robust Model Matching for an Adaptive Optics System
R. Maimaiti, N. Miura, T. Eisaka

Abstract: Atmospheric turbulence is major obstacle to achieve high-resolution imaging of object since telescopes were invented. Adaptive optics is a developing technology, which is commonly used in ground-based astronomical telescopes to remove the effects of atmospheric distortion and improve the performance of optics system. To achieve high-resolution imaging of targets in space, it is of key importance to reduce the effects of atmospheric turbulence by operating a deformable mirror. Various computer control approaches have been applied to overcome this problem. However, these approaches tend to yield high-order complex controllers. In this paper, we propose a simple and tunable low-order robust controller design for an adaptive optics system based on the robust model matching method. The resultant robust compensator can be attached to any kind of existing AO control systems and the robustness can be tuned easily. Simulation and experimental results are presented demonstrating the efficiency of the proposed design.
 

Adapting Correction Factors in Probability Distribution Function for VAD Improvement
H. Farsi, M. A. Mozaffarian, H. Rahmani

Abstract: One of the new methods that used in Voice activity detection (VAD) systems is estimating the Probability Distribution Function (PDF) of the speech signal. This estimation becomes hard in noisy environments especially low value of Signal-to-Noise Ratios (SNR). This paper studies on three types of PDFs and selects one of them to modify and approximate the original signal. Then we compare the results of this PDF before and after modification.
 

Estimation of Control Parameters of Self-Excited Induction Generator
K. S. Sandhu, Dheeraj Joshi

Abstract: Operation of induction generator in self-excited mode is found to be useful in contrast to grid connected mode due to its ability to generate power for wide range of operating speeds. However such operations results in to a frequent variations in terminal voltage and frequency in the absence of any control strategy. Therefore such machines need a proper control to maintain its output quality in terms of generated voltage and frequency. In the present paper a new model has been proposed to estimate the control parameters of self-excited induction generators. Proposed modeling requires the solution of quadratic equation in operating speed and a simple expression for excitation capacitance. Simulated results as obtained using proposed model are compared with experimental results on two test machines. A close agreement between simulated and experimental results proves the validity of proposed modeling.
 

    Paper Title, Authors, Abstract (Issue 2, Volume 3, 2009)

Pages

FPGA Implementation of Ternary Pulse Compression Sequences with Superior Merit Factors
N. Balaji, K. Subba Rao, M. Srinivasa Rao

Abstract: Ternary codes have been widely used in radar and communication areas, but the synthesis of ternary codes with good merit factor is a nonlinear multivariable optimization problem, which is usually difficult to tackle. To get the solution of above problem many global optimization algorithms like genetic algorithm, simulated annealing, and tunneling algorithm were reported in the literature. However, there is no guarantee to get global optimum point. In this paper, a novel and efficient VLSI architecture is proposed to design Ternary Pulse compression sequences with good Merit factor. The VLSI architecture is implemented on the Field Programmable Gate Array (FPGA) as it provides the flexibility of reconfigurability and reprogramability. The implemented architecture overcomes the drawbacks of non guaranteed convergence of the earlier optimization algorithms.
 

A Petri Nets Approach for Hybrid Systems Modeling
Mircea Adrian Drighiciu, Anca Petrisor, Marius Popescu

Abstract: This paper focuses on the modeling of hybrid systems with autonomous commutation of the model generated by a hysteresis phenomenon through a particular Petri Nets structures, called Modified Petri Nets (MPN). The main goal of this approach is to get a formal description language for such hybrid systems, which combines the advantages of a graphical description with the possibility of a transparent visualization, simulation and analysis. Hence, several enhancements were proposed. The first of them combines the classical discrete Petri Net approach and the concept of continuous Petri Nets, having as result a class called Hybrid Petri Nets (HPN). In the second enhancement, the aspect of the system complexity was approached by introducing object oriented concepts, like encapsulation and information hiding. In this way, the resulting Hybrid Object Nets (HON) combines the advantages of Hybrid Petri Nets with those of the object-oriented paradigm. The proposed concepts are illustrated with a case study, which refers to a classical temperature control process in a room, using a thermostat with anticipative resistance.
 

Modeling and Control of Micro-Turbine Based Distributed Generation System
Ashwani Kumar, K. S. Sandhu, S. P. Jain, P. Sharath Kumar

Abstract: Micro turbine generation is currently attracting lot of attention to meet users need in the distributed generation market due to the deregulation of electric power utilities, advancement in technology, environmental concerns. In this paper modeling of micro-turbine distributed generation system has been implemented and a new converter controller for a simulation of dynamic model of a micro-turbine generation system (MTG) has been proposed. The converter controllers are built on the dq synchronous frame. The converter controller models are implemented in the MATLAB / SIMULINK using SIMPOWER Systems library. The performance of the implemented MTG model is studied with an isolated load considering RL, LCL filter without and with reactive power injection into the system.
 

PIC-Based Multi-Channel PWM Signal Generation Method and Application to Motion Control of Six Feet Robot Toy
Chin-Pao Hung, Wei-Ging Liu, Hong-Jhe Su, Jia-Wei Chen, Bo-Ming Chiu

Abstract: The aim of this research considered in this paper is to show a novel multi-channel PWM (pulse width modulation) signal generation method for the multi-joint RC robot driving. Integrating the I/O pins of the microcontroller and the interrupt function of the built-in timer, the maximum PWM channel number is identical to the number of I/O pins and can be used to drive the multi-joint robot. Differ to traditional polling scheme; the multiple channel PWM signals are synchronous. Applying this novel scheme to the 18 joints RC robot control, without any other extra chips or components, the smoothing motion control demonstrated the feasibility of the proposed scheme. Also, a user friendly interface is developed to benefit the motion control planning. User planned the walking path and downloaded it from PC to PIC microcontroller via RS232 protocols. Then the PIC microcontroller runs the motion control independently.
 

System Identification based Kepstrum Analysis and Real-Time Application to Noise Cancellation
Jinsoo Jeong

Abstract: This paper presents analysis of kepstrum (known elsewhere as complex cepstrum) and its real-time application to noise cancellation. System identification based kepstrum method estimates the ratio of acoustic path transfer functions between two microphones and it is processed in an efficient way for real-time processing. Its front-end application to speech enhancement method will be shown that it effectively cancels echoes and hence reverberation in a noisy environment with computational simplicity on kepstrum processing for a real-time application. Furthermore, from the test based on the three different microphones configuration, it will be shown that kepstrum provides a better noise reduction ratio in endfire microphones configuration to a simple speech enhancement method, G-J beamformer structure.
 

Analysis of System Identification and Modified Application to Two-Microphone Speech Enhancement
Jinsoo Jeong

Abstract: This paper provides analysis of identification of acoustic transfer functions between two microphones and investigation of modified application from two-microphone adaptive noise cancelling and beamforming methods. Based on this, we will perform real-time performance comparisons to obtain the best solution to speech enhancement and noise cancellation. Experiments are processed by software implementation using LabVIEW in a real environment, which is typical indoor office with moderate reverberation condition. The speech performances are analyzed in time and frequency domains using both stationary and nonstationary noises. The analysis on the three type of microphones configuration and computational complexity on NLMS algorithm and TDOA function have also been investigated, which could give rise to fundamental basis for further real-time applications using two-microphone as well as hardware prototype implementation of digital adaptive hearing aids.
 

    Paper Title, Authors, Abstract (Issue 3, Volume 3, 2009)

Pages

Efficient FPGA Implementation of FFT/IFFT
Ahmed Saeed, M. Elbably, G. Abdelfadeel, M. I. Eladawy

Abstract: The Fast Fourier Transform (FFT) and its inverse (IFFT) are very important algorithms in signal processing, software-defined radio, and the most promising modulation technique; Orthogonal Frequency Division Multiplexing (OFDM). This paper explains the implementation of radix-22 single-path delay feedback pipelined FFT/IFFT processor. This attractive architecture has the same multiplicative complexity as radix-4 algorithm, but retains the simple butterfly structure of radix-2 algorithm. The implementation was made on a Field Programmable Gate Array (FPGA) because it can achieve higher computing speed than digital signal processors, and also can achieve cost effectively ASIC-like performance with lower development time, and risks. The processor has been developed using hardware description language VHDL on an Xilinx xc5vsx35t and simulated up to 465MHz and exhibited execution time of 0.135μS for transformation length 256-point. This results show that the processor achieves higher throughput and lower area and latency.
 

Exploiting the Vth Behavior to Design CMOS Voltage References and Temperature Sensors
Wellington Avelino do Amaral, Jose Antonio de Siqueira Dias, Wilmar Bueno de Moraes

Abstract: The objective of this work is to design a CMOS voltage reference and a temperature sensor based on threshold voltage summation. An original circuit architecture was used. The circuit uses a threshold voltage extractor, a start-up and an operational amplifier. The circuit was fabricated using a 0.35 μm CMOS technology and presented a variation of 11 ppm/0C in the 27 0C to 120 0C temperature range. The temperature sensor presented a sensitivity of 1mV/ 0C when operated in the same temperature range.
 

EEG Signal Analysis for Silent Visual Reading Classification
I. Oliveira, O. Grigori, N. Guimaraes

Abstract: This paper describes a study regarding the detection of silent visual reading mental activity through electroencephalogram (EEG) analysis and processing. Our work is in the context of human computer interaction research field, and we pretend to use EEG signals in applications to assist and analyze reading tasks. The need of users to be constantly and tightly coupled with the applications is being highly stimulated by the design of universally-accessible interactive systems. In this context, the use of biomedical signals has become an emerging area. Visual reading has a great interest to us, since it is a frequent activity while users interact with applications. Users will stop reading whether they feel disturbed or lost, or lose their interest, or even if application visual characteristics (such as font size and color) make it difficult. The analysis of visual reading flow will allow a better understanding of users mind while interacting with applications and help to objectify some still subjective usability tests. The work focuses on building reliable capture and preprocessing procedures, extracting relevant features and testing simple learning algorithms. The detection process uses left hemisphere EEG signals, which are referred to as being the relevant brain area for this type of tasks. The signals were processed to extract the power spectrum density of delta, theta, and alpha rhythms, known frequencies of this type of signals. We also present two real time demonstration applications of assisted reading.
 

Particle Swarm Optimization Based Tuning of Extended Kalman Filter for Manoeuvring Target Tracking
Ravi Kumar Jatoth, T. Kishore Kumar

Abstract: Kalman filter is a well known adaptive filtering Algorithm, widely used for target tracking applications. When the system model and measurements are non linear, variation of Kalman filter like extended Kalman filter (EKF) is used. For obtaining reliable estimate of the target state, filter has to be tuned before the operation (off line).Tuning an EKF is the process of estimation of the noise covariance matrices from process data. In practical applications, due to unavailable measurements of the process noise and high dimensionality of the problem tuning of the filter is left for engineering intuition. In this paper, tuning of the EKF is investigated using Particle Swarm Optimization (PSO). The simulation results show the superiority of the PSO tuned EKF over the conventional EKF.
 

Secret Image Sharing based on Vector Quantization
Lee Shu-Teng Chen, Wei-Kai Su, Ja-Chen Lin

Abstract: This paper proposes an (r, n) threshold secret image sharing scheme based on Vector Quantization (VQ). By using the host images as the VQ codebooks, the VQ indices of the secret image is computed and then shared among the n shadows. The created n shadows and the mixed information of the VQ codebooks are hidden in the original host images to form the n stego images. During the recovery phase, the secret image with VQ quality can be reconstructed by any r of the n stego images. The proposed method is therefore missing-allowable since n-r stego images can be lost in the recovery phase. Experiments show that the qualities of our stego images and recovered images are all acceptable. Moreover, the proposed method is secure because it is unlikely to reveal the secret image if less than r stego images are intercepted.
 

A Novel Minimal Script for Arabic Text Recognition Databases and Benchmarks
Husni A. Al-Muhtaseb, Sabri A. Mahmoud, Rami S. Qahwahi

Abstract: This paper presents a minimal Arabic text that covers the different basic shapes of Arabic alphabet (viz. standalone, initial, medial, and terminal). It is designed with minimal repetition of character shapes in the minimal text. The novelty of the suggested script could be seen from different perspectives. It enables the collection of handwritten text from different writers with minimized effort and time. It is enough for a writer to write three lines of meaningful Arabic text to cover all possible character shapes, a total of 125 shapes. The written text is designed to have even distribution of letter frequencies. This assures enough samples of all character shapes when text is collected from enough number of writers. The same is true for printed Arabic text. This is especially useful when using large number of features with classifiers that require large number of samples for each category. Hidden Markov Models and Neural networks are two examples of these classifiers. The use of the minimal text enables proper training, as all Arabic character shapes are present with adequate frequency, hence resulting in higher recognition rates. This is not the case with natural text where the frequency of some Arabic characters differ widely, where in some cases 100 folds or more. The proposed minimal text may be used to build a data base of handwritten Arabic text collected of many writers. This covers the need for a database in the research of Arabic handwritten text recognition and benchmarking.
 

Temperature Investigation in Contact Pantograph - AC Contact Line
Constantin-Florin Ocoleanu, Ioan Popa, Gheorghe Manolea, Alin-Iulian Dolan, Serghie Vlase

Abstract: In this paper we performed a thermal analyses using experimental determination of temperature in contact pantograph - AC contact line. The pantograph is asymmetric EPC type and the contact line wire is TF 100 type, both used in Romanian Electric Railways. The influence on the temperature value of the small contact area between two collector strips of pantograph and contact wire is pointed out.
 

Design of Three-Stage Nested-Miller Compensated Operational Amplifiers Based on Settling Time
Hamed Aminzadeh, Khalil Mafinezhad, Reza Lotfi

Abstract: Settling performance of operational amplifiers (opamps) is of great importance in analog signal-processing applications. Among different architectures, three-stage amplifiers are gaining more attention between analog circuit designers of modern technologies with small supply voltages where few devices can be stacked. Previous attempts to design and optimize a three-stage opamp based on settling time suffer from lack of a comprehensive analysis of the settling behavior and closed-form relationships between settling time/error and other parameters. In this paper, a thorough analysis of the settling response of threestage nested-Miller-compensated opamps, including linear and non-linear sections, is presented. Based on this analysis, a design methodology is presented which determines the circuit requirements to achieve a desired settling time/error. It allows optimizations in power consumption and area based on settling time.
 

    Paper Title, Authors, Abstract (Issue 4, Volume 3, 2009)

Pages

An Efficient Search Range Decision Algorithm for Motion Estimation in H.264/AVC
Mohammed Golam Sarwer, Q. M. Jonathan Wu

Abstract: Variable block size motion estimation (VBME) is a new feature introduced in H.264/AVC video coding standard. VBME plays a significant rule in achieving outstanding performance in compression efficiency and video quality. However, the VBME is the most time consuming part of H.264/AVC encoder. In order to reduce computations in motion estimation module, this paper presents a novel adaptive search area selection method by utilizing the information of the previously computed motion vector differences (MVDs). The direction of picture movement of the previously computed blocks is also considered for search area selection. In this algorithm, narrow search ranges are chosen for areas in which little motion occurs and wide ranges are chosen for areas of significant motion. Experimental results show that the proposed algorithm provides significant improvement in coding speed with negligible objective quality degradation compared to the full search motion estimation method adopted by H.264/AVC reference software.
 

Endmember Transformation and Replacement in Real Time Hyperspectral Unmixing
Masoud Farzam, Soosan Beheshti

Abstract: For much of the past decade Hyperspectral Imaging (HSI) systems have gained considerable attention among researchers. Recent improvements in Optics have expanded the applications of HSI systems. Real time processing of extensive volumes of Hyperspectral data calls for more efficient and accurate real time algorithms. In current algorithms, speed comes at the expense of accuracy. Nevertheless, our proposed Ultra Fast Transition and Replacement (UFTR) approach shows a substantial improvement to the processing speed while also increasing the accuracy of the present methods. In the UFTR algorithm, Hyperspectral components’ signatures, known as Endmembers, are estimated in an iterative approach. In each iteration, a linear transformation of data into the abundance vectors is calculated. This iterative process causes the speed of the algorithm to be extraordinarily fast. To improve the accuracy, a correlation based approach is used to project the estimated Endmembers into the library spectrum. Accurate abundance vectors are calculated using the final transition matrix and the chosen Endmembers from the library. UFTR simulation results show that in low-SNR applications, the accuracy can be improved up to 15% and the speed is 10 to 50 times faster compared to the existing methods for a data cube of 4096 pixel with 224 bands. Furthermore, unlike many existing approaches, UFTR processing time dependency on the noise level is quite low. UFTR is definitely a departure from the trade-off between speed and accuracy and has a great potential for applications in the real time Hyperspectral imaging.
 

Detection of the Number of Signal Sources in the Hyperspectral Data
Majid Mohamady Oskouei, Rashed Poormirzaee

Abstract: This study investigates and compare different methods to estimate the number of signal sources in the hyperspectral data. To achieve an accurate map of mineral distributions in the study area by means of the spectral analysis of Hyperion data, the number of endmembers was computed by different methods. This process is also known as determination of virtual dimensionality of the image. Estimation of Virtual Dimensionality of data or in other words, the number of detectable endmembers from data is very important task in hyperspectral imagery. If this estimated number doesn’t meet the reality, final estimation of mineral abundances will be erroneous. The results established that principle component analysis underestimates the virtual dimensionality of data. This is reasonably due to lower abundances of some minerals on the earth surface that will be considered as unimportant principle components because of their lower energy fraction in the total radiance measured at sensor. The higher order statistical method on the other hand, showed better performance. This method uses Neyman–Pearson detection theory and its estimation is more realistic.