Hamid Nooralizadeh; Behnam Babazadeh Daryan
Volume 11, Issue 2 , June 2017
Abstract
An ultra-wideband (UWB) common gate-common source (CG-CS) low-noise amplifier (LNA) in a 0.18μm CMOS technology is presented in this paper. To obtain a high and flat power gain with low noise and good input impedance matching in the entire 3.1–10.6 GHz UWB band among low power consumption, a capacitive ...
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An ultra-wideband (UWB) common gate-common source (CG-CS) low-noise amplifier (LNA) in a 0.18μm CMOS technology is presented in this paper. To obtain a high and flat power gain with low noise and good input impedance matching in the entire 3.1–10.6 GHz UWB band among low power consumption, a capacitive cross-coupling fully differential amplifier with the current-reuse technique is proposed. The current–reuse technique is used to achieve a wideband and reduce power consumption. The capacitor cross coupling technique is used to gm-boosting and hence to improve the NF of the amplifier. Therefore, the dependency between noise figure (NF) and input impedance matching is reduced. The proposed CG-CS amplifier has a fairly low NF compared with the other previous works in similar technology. In addition, a good power gain over all bandwidth and a high isolation with good input/output impedance matching are achieved. The minimum NF is 1.8 dB, the maximum power gain is 14.2 dB, the inverse gain is <-50 dB, the input and output matching S11 and S22 are <-10.3 dB and <-11.3 dB, respectively. Moreover, the input third-order intercept point (IIP3) is -5 dBm with core power consumption of 10.1 mW and supply voltage of 1.8 V.
Javad Chaharlang; Mohammad Mosleh
Volume 11, Issue 2 , June 2017
Abstract
Quantum-dot Cellular Automata (QCA) is a computational technology that can be used to construct nanoscale circuits. Nowadays, this technology is a good alternative for CMOS technology due to features such as high speed, low occupied area and low power consumption. Mmemory is utilized as one of the basic ...
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Quantum-dot Cellular Automata (QCA) is a computational technology that can be used to construct nanoscale circuits. Nowadays, this technology is a good alternative for CMOS technology due to features such as high speed, low occupied area and low power consumption. Mmemory is utilized as one of the basic elements in digital circuit design hence the design and optimization of high-speed RAM memory cells have become one of the most attractive research areas; in the realm of QCA. In this paper, we present a comprehensive investigation on RAM memories. For this purpose, the proposed schemes in terms of functionality, the number of cell consumption, and latency are implemented and compared using QCA Designer software. The results show that some of the proposed schemes show better performance in terms of parameters such as occupied area and delay. Nevertheless, they are still suffering from less stability; hence introducing an optimum scheme is infeasible.
Mohammad Javad Aranian; Moein Sarvaghad-Moghaddam; Monireh Houshmand
Volume 11, Issue 2 , June 2017
Abstract
Curse of dimensionality is one of the biggest challenges in classification problems. High dimensionality of problem increases classification rate and brings about classification error. Selecting an effective subset of features is an important point in analyzing correlation rate in classification issues. ...
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Curse of dimensionality is one of the biggest challenges in classification problems. High dimensionality of problem increases classification rate and brings about classification error. Selecting an effective subset of features is an important point in analyzing correlation rate in classification issues. The main purpose of this paper is enhancing characters recognition and classification, creating quick and low-cost classes, and eventually recognizing Persian handwritten characters more accurately and faster. In this paper, to reduce feature dimensionality of datasets a hybrid approach using artificial neural network, genetic algorithm and quantum genetic algorithm is proposed that can be used to distinguish Persian handwritten letters. Implementation results show that proposed algorithms are able to reduce number of features by 19% to 49%. They also show that recognition and classification accuracy of resulted subset of features has risen, by 7/31%, comparing to primitive dataset.
Volume 11, Issue 2 , June 2017
Abstract
Data clustering is a popular analysis tool for data statistics in several fields, including includes pattern recognition, data mining, machine learning, image analysis and bioinformatics, in which the information to be analyzed can be of any distribution in size and shape. Clustering is effective as ...
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Data clustering is a popular analysis tool for data statistics in several fields, including includes pattern recognition, data mining, machine learning, image analysis and bioinformatics, in which the information to be analyzed can be of any distribution in size and shape. Clustering is effective as a technique for discerning the structure of and unraveling the complex relationship between massive amounts of data. See-See partridge chick’s optimization (SSPCO) algorithm is a new optimization algorithm that is inspired by the behavior of a type of bird called see-see partridge. We propose chaotic map SSPCO optimization method for clustering, which uses a chaotic map to adopt a random sequence with a random starting point as a parameter, the method relies on this parameter to update the positions and velocities of the chicks. In the study, twelve different clustering algorithms were extensively compared on thirteen test data sets. The results indicate that the performance of the Chaotic SSPCO method is significantly better than the performance of other algorithms for data clustering problems.
Mohsen Shahrezaee
Volume 11, Issue 2 , June 2017
Abstract
Image segmentation has been widely used in different applications of the image processing. It The main objective of image segmentation is to subdivide the input images to their main components. Generally, the main purpose of the segmentation is to simplify or change an image representation into something ...
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Image segmentation has been widely used in different applications of the image processing. It The main objective of image segmentation is to subdivide the input images to their main components. Generally, the main purpose of the segmentation is to simplify or change an image representation into something that is more meaningful and easier to analyze. In this paper, World Cup Optimization Algorithm (WCO) is proposed to classify the main components of an image (pixels) into different groups. In the experiment, the proposed method performance is measured by comparing with Otsu as a classic method and GA based and APSO based image segmentation algorithms as the heuristic based algorithms for segmentation. When compared with the other segmentation methods, the proposed WCO based method achieved good performance. The final efficiency of the proposed system is compared with the described methods. Experimental results show that the proposed method has overcome the others in the performance.
Ali Ghaffari; Majid Babaei
Volume 11, Issue 2 , June 2017
Abstract
The Cache efficiency is considered to be one of the major challenges in multi-core processors. Hence, using cache space in such processors should be meticulously managed by each of the cores. This paper addresses the issue of cache re-access and proposes an algorithm which divides the last level of cache ...
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The Cache efficiency is considered to be one of the major challenges in multi-core processors. Hence, using cache space in such processors should be meticulously managed by each of the cores. This paper addresses the issue of cache re-access and proposes an algorithm which divides the last level of cache into local and global share for the cores. The rationale behind the proposed algorithm is to activate or deactivate the ways of cache for any intended core. Consequently, the collision between cores is reduced and each of the cores can use the cache space dynamically. To simulate the proposed algorithm, the researchers used three groups of applications and the obtained results were examined and evaluated in two stages. The first phase is involved with the number of active ways in cache for each core. It should be highlighted that the proposed algorithm, in the merged state, was able to enhance the active ways up to 19%. In the second phase, cache miss rate was taken into consideration and it was observed that about 7% improvement was achieved in this stage.
Alireza Ahmadimanesh; Mohsen Kalantar
Volume 11, Issue 2 , June 2017
Abstract
In this paper, a new reactive power market structure is studied and presented. Active power flow by itself causes active and reactive losses. Considering such losses after active power market clearing and in the reactive power market procedure without paying any costs is the main purpose of this paper. ...
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In this paper, a new reactive power market structure is studied and presented. Active power flow by itself causes active and reactive losses. Considering such losses after active power market clearing and in the reactive power market procedure without paying any costs is the main purpose of this paper. For this purpose, new methodologies for reactive power structure are proposed which the reactive losses are considered before market closing. Hence, this study tries to improve reactive power market and create fair competition in reactive power generation through improving the market structure. Also, in this work, the cost payment function of synchronous generators, which has an important influence on reactive power market, is modified. In order to stimulate and describe the proposed methods in the implementation of reactive power market, Cigre 32 bus test system is applied and the proposed methods. As will be shown, the total payment by ISO will be reduced by using the proposed methods.
Mohsen Yoosefi Nejad; Mohammad Mosleh
Volume 11, Issue 2 , June 2017
Abstract
Quantum-dot Cellular Automata (QCA), is a contemporary nanotechnology for manufacturing logical circuits which brings less power consumption, smaller circuit size, and faster operation. In this technology, logical gates are composed of nano-scale basic components called cells. Each cell consists of four ...
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Quantum-dot Cellular Automata (QCA), is a contemporary nanotechnology for manufacturing logical circuits which brings less power consumption, smaller circuit size, and faster operation. In this technology, logical gates are composed of nano-scale basic components called cells. Each cell consists of four quantum-dot arranged in a square pattern. Diagonal arrangement of two extra electrons resembles two logical states 0 and 1. Majority gate and inverter gate are considered as the two most fundamental building blocks of QCA. The effect of cells on their neighbor cells enables designing more diverse circuits. Multiplexer is a key component in most computer circuits. Researchers have presented various QCA designs for multiplexers since the introduction of QCA. In this research all presented designs are simulated in QCA Designer Version 2.0.3 and investigated from different aspects such as number of cells, size, types of components used in circuit, number of layers, and number of cycles for producing output.
