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Design Of Analog Cmos Integrated Circuits

Thank you very much for downloading design of analog cmos integrated circuits. Maybe you have knowledge that, people have look hundreds times for their favorite novels like this design of analog cmos integrated circuits, but end up in malicious downloads. Rather than reading a good book with a cup of coffee in the afternoon, instead they cope with some malicious virus inside their laptop. design of analog cmos integrated circuits is available in our book collection an online access to it is set as public so you can download it instantly. Our digital library saves in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Merely said, the design of analog cmos integrated circuits is universally compatible with any devices to read.

Whale Optimization Algorithm (WOA) is an optimization algorithm developed by Mirjalili and Lewis in 2016. An overview of WOA is described in this paper, rooted from the bubble-net hunting strategy, besides an overview of WOA applications that are used to solve optimization problems in various categories. The best solution has been determined to make something as functional and effective as possible through the optimization process by minimizing or maximizing the parameters involved in the problems. Research and engineering attention have been paid to Meta-heuristics for purposes of decision-making given the growing complexity of models and the needs for quick decision making in the engineering. An updated review of research of WOA is provided in this paper for hybridization, improved, and variants. The categories included in the reviews are Engineering, Clustering, Classification, Robot Path, Image Processing, Networks, Task Scheduling, and other engineering applications. According to the reviewed literature, WOA is mostly used in the engineering area to solve optimization problems. Providing an overview and summarizing the review of WOA applications are the aims of this paper.

A comprehensive survey: Whale Optimization Algorithm and its applications

Oxford University Press in Africa, 1927â80

This research’s genesis is in two aspects: first, a guaranteed solution for mitigating the grey wolf optimizer’s (GWO) defect and deficiencies. Second, we provide new open-minding insights and deep views about metaheuristic algorithms. The population-based GWO has been recognized as a popular option for realizing optimal solutions. Despite the popularity, the GWO has structural defects and uncertain performance and has certain limitations when dealing with complex problems such as multimodality and hybrid functions. This paper tries to overhaul the shortcomings of the original process and develops a GWO variant enhanced with a covariance matrix adaptation evolution strategy (CMAES), levy flight mechanism, and orthogonal learning (OL) strategy named GWOCMALOL. The algorithm uses the levy flight mechanism, orthogonal learning strategy, and CMAES to bring more effective exploratory inclinations. We conduct numerical experiments based on various functions in IEEE CEC2014. It is also compared with 10 other algorithms with competitive performances, 7 improved GWO variants, and 11 advanced algorithms. Moreover, for more systematic data analysis, Wilcoxon signed-rank test is used to evaluate the results further. Experimental results show that the GWOCMALOL algorithm is superior to other algorithms in terms of convergence speed and accuracy. The proposed GWO-based version is discretized into a binary tool through the transformation function. We evaluate the performance of the new feature selection method based on 24 UCI data sets.​ Experimental results show that the developed algorithm performs better than the original technique, and the defects are resolved. Besides, we could reach higher classification accuracy and fewer feature selections than other optimization algorithms. A narrative web service at http://aliasgharheidari.com will offer the required data and material about this work.

Orthogonal learning covariance matrix for defects of grey wolf optimizer: Insights, balance, diversity, and feature selection

In this paper, a new population based hybrid meta-heuristic algorithm called the Hybrid Whale-Particle Swarm Optimization Algorithm (HWPSO) for solving complex optimization problems has been proposed. The proposed algorithm tries to overcome the limitations associated in a Particle Swarm Optimization (PSO) exploration phase i.e. Stagnation Effect, by hybridizing with a whale optimization algorithm (WOA) in a novel way as WOA has been reported to have very good exploration capability. During hybridization, two novel techniques have been employed, namely ‘Forced’ Whale and ‘Capping’ Phenomenon. The ‘Forced’ WOA is introduced in exploration phase and it enables the WOA to guide PSO for better local optima avoidance and concurrently a new ‘Capping’ phenomenon is employed which restricts the WOA search mechanism during exploitation phase, thereby converging the solution faster to a global optimum value. The performance of the proposed HWPSO has tested on 18 benchmark mathematical functions and 3 Electronics Design Optimization problems. The simulation results indicate that the proposed algorithm outperforms many state of the art algorithms by achieving a better optima with a very low standard deviation for most of the benchmark functions used. The effectiveness of the proposed HWPSO has been also validated by statistical as well as complexity analysis. The performance of HWPSO algorithm is also found to be satisfactory in all three cases of electronics design optimization problems, which have been further validated with standard design tools and found to be in close agreement with each other.

HWPSO: A new hybrid whale-particle swarm optimization algorithm and its application in electronic design optimization problems

With an explosive growth of the mobile applications and emerging of cloud computing concept, the Mobile Cloud Computing (MCC) has become a potential technology for the mobile service users. MCC integrates the technology of cloud computing with mobile environment and has taken part of major discussion thread in the IT world since 2009. The ABI Research predicts that the number of mobile cloud computing subscribers is expected to grow from 42.8 million (1.1% of total mobile users) in 2008 to 998 million (19% of total mobile users) in 2014. Despite of this hype achieved by mobile cloud computing, the growth of mobile cloud computing subscribers is still below expectations. According to the recent survey conducted by the International Data Corporation, most IT Executives and CEOs are not interested in adopting such services due to the drawbacks associated with this (e.g., battery life, storage, and bandwidth), environment (e.g., heterogeneity, scalability, and availability), and security (e.g., reliability and privacy). In spite of various efforts to overcome these, there are a number of loopholes and challenges that still exist in the security policies of mobile cloud computing. This paper will give a review of various challenges in this field and measures to overcome such.

A Review and Research Towards Mobile Cloud Computing

This Paper Presents the design and simulation of RF MEMS switch taken on Microstrip patch antenna loaded with the circular type CSRR. The Tunability of the patch antenna is achieved when the two switches moves from upstate to down state arranged on the feeding line provided with the CPW. The actuation voltage required to move the switch downwards is 7.6 V. The switch operates at transition time of 0.8 µsec with the capacitance ratio 10. The return loss (S11) of antenna − 28.67 dB is observed at the frequency of 19 GHz when one switch is in on state and at 16 GHz frequency the S11 of − 29.31 dB is achieved by actuating the 2 switches at a time, which gives the reconfigurable property of the antenna. The antenna provides 2 GHz and 5 GHz frequency shift when single and both the switches are in on state. The antenna can be tuned for various applications in the range of 15–30 GHz frequency. The characteristics of switch has been observed by simulating the switch design in FEM tool and results have been compared with theoretical calculations. The tunable characteristics of antenna has been observed and presented by using HFSSV.13 tool.

Design and simulation of fixed–fixed flexure type RF MEMS switch for reconfigurable antenna

The internet of things (IoT) is now an in-demand technology that has been adopted in various applications and includes various embedded devices, sensors and other objects connected to the Internet. Due to the rapid development of this technology, it covers a significant portion of the research interests nowadays. IoT devices are typically designed for collecting different types of data from various sources and transmitting them in digitized form. However, data security is the burning issue in the IoT technology, which can broadly impact the privacy of crucial data. In this regard, a new lightweight encryption method called LRBC has been proposed in this work for resource constraint IoT devices which can provide data security at the sensing level. The LRBC has used the structural advantages of both substitution–permutation network (SPN) and Feistel structure together to achieve better security. Furthermore, the proposed method has been tested on NEXYS 4 DDR FPGA (Artix-7) trainer kit and implemented for application specific integrated circuit (ASIC) chip on TSMC 65 nm technology. The proposed algorithm consumes very less power of 11.40 μW and occupies a 258.9 GE (Gate Equivalent) area. Besides, a thorough security analysis shows that the proposed scheme ensures high security against various attacks with robustness. Moreover, the average avalanche effect of LRBC is found to be 58% and 55.75% concerning plaintext and key, respectively.

LRBC: a lightweight block cipher design for resource constrained IoT devices

In a flash ADC, output of the comparators constitute the thermometer code. This thermometer code is converted to binary code with the help of a thermometer to binary decoder using a ROM. However, this conversion scheme suffers from metastability and bubble errors. A novel ROM architecture has been proposed which suppresses metastability, both first and second order bubble errors. It eliminates the need of an error correction circuit in the front end of the ROM thereby reducing power consumption, area requirement and removing the delay associated with the additional stage. This architecture also eliminates the need of Gray coded ROM and Gray to binary converter thereby making the circuit simpler.

Krishna Lal Baishnab

Papers

HWPSO: A new hybrid whale-particle swarm optimization algorithm and its application in electronic design optimization problems

A Review and Research Towards Mobile Cloud Computing

Design and simulation of fixed–fixed flexure type RF MEMS switch for reconfigurable antenna

LRBC: a lightweight block cipher design for resource constrained IoT devices

A novel ROM architecture for reducing bubble and metastability errors in high speed flash ADCs