2010 13th International Conference on Computer and Information Technology (ICCIT)最新文献_第5页

A parametric formulation to Detect Speech Activity of noisy speech using EDON 一种用EDON检测含噪语音活动的参数化方法

2010 13th International Conference on Computer and Information Technology (ICCIT) Pub Date : 2010-12-01 DOI: 10.1109/ICCITECHN.2010.5723864

M. Hasan, Md. Ekramul Hamid

引用次数: 2

A novel two-tier multiple sequence alignment algorithm 一种新的双层多序列比对算法

2010 13th International Conference on Computer and Information Technology (ICCIT) Pub Date : 2010-12-01 DOI: 10.1109/ICCITECHN.2010.5723819

Md. Sowgat Ibne Mahmud, Md. Akhter Hosen, Md. Saroer-E-Azam, M. Mottalib, H. A. Al-Mamun

引用次数: 1

On the performance of Recurring Multistage Evolutionary Algorithm for continuous function optimization 连续函数优化的循环多阶段进化算法性能研究

2010 13th International Conference on Computer and Information Technology (ICCIT) Pub Date : 2010-12-01 DOI: 10.1109/ICCITECHN.2010.5723830

Mohammad Shafiul Alam, Md Wasi Ul Kabir, M. Islam

引用次数: 3

An approximation algorithm for bounded degree closest phylogenetic 2nd root problem 有界度最接近系统发育二根问题的近似算法

2010 13th International Conference on Computer and Information Technology (ICCIT) Pub Date : 2010-12-01 DOI: 10.1109/ICCITECHN.2010.5723821

Md. Ahsanur Rahman, Md. Rafiqul Islam

引用次数: 0

Performance evaluation of MLPC and MFCC for HMM based noisy speech recognition 基于HMM的MLPC和MFCC噪声语音识别性能评价

2010 13th International Conference on Computer and Information Technology (ICCIT) Pub Date : 2010-12-01 DOI: 10.1109/ICCITECHN.2010.5723868

M. Rahman, M. Islam

引用次数: 6

Curvelet texture based face recognition using Principal Component Analysis 基于主成分分析的曲线纹理人脸识别

2010 13th International Conference on Computer and Information Technology (ICCIT) Pub Date : 2010-12-01 DOI: 10.1109/ICCITECHN.2010.5723827

Shafin Rahman, S. M. Naim, Abdullah Al Farooq, M. Islam

{"title":"Curvelet texture based face recognition using Principal Component Analysis","authors":"Shafin Rahman, S. M. Naim, Abdullah Al Farooq, M. Islam","doi":"10.1109/ICCITECHN.2010.5723827","DOIUrl":"https://doi.org/10.1109/ICCITECHN.2010.5723827","url":null,"abstract":"A vital issue for face recognition is to represent a face image by effective and efficient features. To-date a numerous feature extraction techniques have been proposed in the literature. Among them, content based image retrieval (CBIR) using curvelet transform captures accurate texture features to represent the image. In this paper, we propose a novel face recognition method that uses curvelet texture features for face representation. Features are computed by low order statistics like mean and standard deviation of transformed face images. Since the spectral domain of curvelet has no hole or overlap, there is no loss of frequency information in face images. Moveover, such feature representation has considerably low dimension. Thus, computation within the face-space becomes easier. Furthermore, the dimension of features is independent of face image resolution. As a result, it can support face images of different resolution as input. To build the classifier, we apply PCA on the concatenated feature representation of subdivisions. We test our system with 4 and 5 levels of scales of curvelet transform. We also experiment by dividing the face image into different number of sub-divisions on three standard databases. The experimental results confirm that curvelet texture features achieve satisfactory performance for face recognition.","PeriodicalId":149135,"journal":{"name":"2010 13th International Conference on Computer and Information Technology (ICCIT)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114682818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 14

Self-adaptation of mutation step size in Artificial Bee Colony algorithm for continuous function optimization 连续函数优化人工蜂群算法中突变步长的自适应

2010 13th International Conference on Computer and Information Technology (ICCIT) Pub Date : 2010-12-01 DOI: 10.1109/ICCITECHN.2010.5723831

Mohammad Shafiul Alam, Md Wasi Ul Kabir, M. Islam

{"title":"Self-adaptation of mutation step size in Artificial Bee Colony algorithm for continuous function optimization","authors":"Mohammad Shafiul Alam, Md Wasi Ul Kabir, M. Islam","doi":"10.1109/ICCITECHN.2010.5723831","DOIUrl":"https://doi.org/10.1109/ICCITECHN.2010.5723831","url":null,"abstract":"This paper introduces a novel adaptation scheme of mutation step size for the Artificial Bee Colony algorithm and compares its results with a number of swarm intelligence and population based optimization algorithms on complex multimodal benchmark problems. The Artificial Bee Colony (ABC) is a swarm based optimization algorithm mimicking the intelligent food foraging behavior of honey bees. The proposed scheme dynamically adapts the mutation step size for better exploration and exploitation of the search space. Mutation with large step size is likely to produce large variations which would facilitate better exploration of the undiscovered regions of the search space while small step size usually produces small variations that are better for exploitation of the already found solutions. The appropriateness of small or large steps changes dynamically depending on the current stage and maturity of the ongoing search process as well as the properties of the search space. So, dynamic adaptation of mutation step size is a promising and interesting research direction that has not been explored so far with the ABC algorithm. This paper introduces Artificial Bee Colony with Exponentially Distributed Mutation (ABC-EDM) that incorporates exponential distributions to produce mutation steps with varying lengths and suitably adjusts the current step length. ABC-EDM is compared on a number of benchmark functions with the original ABC algorithm, Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Particle Swarm Inspired Evolutionary Algorithm (PS-EA). Results demonstrate that ABC-EDM performs better optimization with lower dimensionality, but the improvement fades away with increased number of dimensions.","PeriodicalId":149135,"journal":{"name":"2010 13th International Conference on Computer and Information Technology (ICCIT)","volume":"189 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132258051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 24

Bangla phoneme recognition for ASR using multilayer neural network 基于多层神经网络的孟加拉语语音识别

2010 13th International Conference on Computer and Information Technology (ICCIT) Pub Date : 2010-12-01 DOI: 10.1109/ICCITECHN.2010.5723837

Mohammed Rokibul Alam Kotwal, Manoj Banik, Qamrun Nahar Eity, M. N. Huda, G. Muhammad, Y. Alotaibi

引用次数: 10

Dynamic modeling and fuzzy logic control of a two-link flexible manipulator using genetic optimization techniques 基于遗传优化技术的两连杆柔性机械臂动态建模与模糊逻辑控制

2010 13th International Conference on Computer and Information Technology (ICCIT) Pub Date : 2010-12-01 DOI: 10.1109/ICCITECHN.2010.5723894

Tahmina Zebin, M. Alam

{"title":"Dynamic modeling and fuzzy logic control of a two-link flexible manipulator using genetic optimization techniques","authors":"Tahmina Zebin, M. Alam","doi":"10.1109/ICCITECHN.2010.5723894","DOIUrl":"https://doi.org/10.1109/ICCITECHN.2010.5723894","url":null,"abstract":"Flexible manipulator systems exhibit many advantages over their traditional (rigid) counterparts. However, they have not been favored in production industries due to its obvious disadvantages in controlling the manipulator. This paper presents theoretical investigation into the dynamic modeling and characterization of a constrained two-link flexible manipulator, by using finite element method. The final derived model of the system is simulated to investigate the behavior of the system. A Genetic Algorithm (GA) based hybrid fuzzy logic control strategy is also developed to reduce the end-point vibration of a flexible manipulator without sacrificing its speed of response. An uncoupled fuzzy logic controller approach is employed with individual controllers at the shoulder and the elbow link utilizing hub-angle error and hub-velocity feedback. GA has been used to extract and optimize the rule base of the fuzzy logic controller. The fitness function of GA optimization process is formed by taking weighted sum of multiple objectives to trade off between system overshoot and rise time. Moreover, scaling factors of the fuzzy controller are tuned with GA to improve the performance of the controller. A significant amount of vibration reduction has been achieved with satisfactory level of overshoot, rise time and settling time and steady state error.","PeriodicalId":149135,"journal":{"name":"2010 13th International Conference on Computer and Information Technology (ICCIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130097409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 13

Towards a tableau based high performance automated theorem prover 迈向基于表格的高性能自动定理证明器

2010 13th International Conference on Computer and Information Technology (ICCIT) Pub Date : 2010-12-01 DOI: 10.1109/ICCITECHN.2010.5723892

Zahidul Islam, Ahmed Shah Mashiyat, Kashif Nizam Khan, S. M. M. Karim

引用次数: 2