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1.
A brain-computer interface （BCI） -based electric wheelchair control system was developed, which enables the users to move the wheelchair forward or backward, and turn left or right without any pre-learning. This control system makes use of the amplitude enhancement of alpha-wave blocking in electroencephalogram （EEG） when eyes close for more than 1 s to constitute a BCI for the switch control of wheelchair movements. The system was formed by BCI control panel, data acquisition, signal processing unit and interface control circuit. Eight volunteers participated in the wheelchair control experiments according to the preset routes. The experimental results show that the mean success control rate of all the subjects was 81.3%, with the highest reaching 93.7%. When one subject＇s triggering time was 2.8 s, i.e., the flashing time of each cycle light was 2.8 s, the average information transfer rate was 8.10 bit/min, with the highest reaching 12.54 bit/min. 相似文献
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Anne R. Fitzpatrick Valerie B. Link Wendy M. Yen George R. Burket Kyoko Ito Robert C. Sykes 《Journal of Educational Measurement》1996,33(3):291-314
In one study, parameters were estimated for constructed-response (CR) items in 8 tests from 4 operational testing programs using the l-parameter and 2- parameter partial credit (IPPC and 2PPC) models. Where multiple-choice (MC) items were present, these models were combined with the 1-parameter and 3-parameter logistic (IPL and 3PL) models, respectively. We found that item fit was better when the 2PPC model was used alone or with the 3PL model. Also, the slopes of the CR and MC items were found to differ substantially. In a second study, item parameter estimates produced using the IPL-IPPC and 3PL-2PPC model combinations were evaluated for fit to simulated data generated using true parameters known to fit one model combination or ttle other. The results suggested that the more flexible 3PL-2PPC model combination would produce better item fit than the IPL-1PPC combination. 相似文献
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支持向量机(Support Vector Machine,SVM)在解决小样本、非线性及高维模式识别中具有优势,但核函数的选取没有定论,且其参数对SVM模型的性能起重要作用。针对这些问题,文章建立了基于SVM的分类模型,并通过UCI数据集验证了径向基核函数(Radial Basis Function,RBF)较其他核函数的有效性,其中核参数的选取采用改进的网格搜索法进行寻优。分类实验结果表明,选择RBF核函数的分类准确度较其他核函数提高了2.5%到35%。 相似文献
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Parameters selection in gene selection using Gaussian kernel support vector machines by genetic algorithm 总被引：2，自引：0，他引：2
INTRODUCTION Recent techniques based on oligonucleotide or cDNA microarrays allow the expression level of thousands of genes to be monitored in parallel (Golub et al., 1999). A critically important factor for cancer diagnosis and treatment is the reliable prediction of tumor progression. A remarkable advance for mo- lecular biology and for cancer research is cDNA mi- croarray technology. cDNA microarray datasets havea high dimensionality corresponding to the large number of genes monit… 相似文献
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为了改善传统脑电情绪识别方法需要对脑电信号进行深入了解,且需要人工提取相关特征的缺点,基于深度森林的表征学习能力对脑电样本的时域与频域数据进行自动特征提取,并融合32通道脑电信号的时域特征向量和频域特征向量,通过级联森林对特征作进一步学习。实验结果表明,该方法对效价二分类预测的准确率达到68.4%,查准率达到66.3%,查全率达到89.9%,F1分数达到76.3%;对唤醒度二分类预测的准确率达到68.2%,查准率达到65.8%,查全率达到91.2%,F1分数达到76.4%。通过与DEAP数据集使用EEG信号给出的二分类实验结果进行对比,基于深度森林的脑电情绪识别方法对未知样本的识别准确率高于DEAP的结果。 相似文献
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Classification was selected for use in this investigation because of the central position of process factors in teaching and learning. A twelve section classification program which was based on 12 rules derived from Piaget's analysis of classification was used in the study. The program was produced in both a constructed response (CR) format and in a matching multiple choice (MC) response format. The 36-item classification test was similarly produced in both response modes. Criterion scores on both the CR test and the MC test were collected from each of the 239 grade three subjects following treatment with the CR program, the MC program, or with drawing activities (control). The results of the multivariate and univariate analyses of variance indicated that the program in both response modes enhanced classification achievement although the effects on MC test scores were not consistent across classes, and that each program format enhanced achievement to a greater degree on the test which matched the program response mode. 相似文献
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针对癫痫脑电(EEG)信号的非平稳性和非线性,提出一种基于集合经验模式分解(EEMD)提特征并利用最小二乘支持向量机(LS-SVM)的脑电信号分类方法。首先利用EEMD将EEG信号分成多个经验模式分量,得到各阶本征模式分量(IMF),然后提取有效特征,最后用LS-SVM对其进行分类,实验结果表明,该方法对癫痫发作间歇期和发作期EEG的提特征后分类识别正确率达到98%。 相似文献
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In order to sufficiently exploit the advantages of different signal processing methods, such as wavelet transformation (WT), artificial neural networks (ANN) and expert rules (ER), a synthesized multi-method was introduced to detect and classify the epileptic waves in the EEG data. Using this method, at first, the epileptic waves were detected from pre-processed EEG data at different scales by WT, then the characteristic parameters of the chosen candidates of epileptic waves were extracted and sent into the well-trained ANN to identify and classify the true epileptic waves,and at last, the detected epileptic waves were certificated by ER. The statistic results of detection and classification show that, the synthesized multi-method has a good capacity to extract signal features and to shield the signals from the random noise. This method is especially fit for the analysis of the biomedical signals in biomedical engineering which are usually non-placid and nonlinear. 相似文献
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SVD-LSSVM and its application in chemical pattern classification 总被引：1，自引：0，他引：1
TAO Shao-hui CHEN De-zhao HU Wang-ming 《浙江大学学报(A卷英文版)》2006,7(11):1942-1947
INTRODUCTION Pattern classification is an important problem in the machine learning field and least squares support vector machine (LSSVM) proposed by Suykens is an easy and powerful tool for this problem (Suykens and Vandewalle, 1999a). Only a set of linear equations should be solved during training of an LSSVM, which makes it easy to be realized. LSSVM is based on structural risk minimization (SRM) rule, which en- hances its generalization ability. SRM rule requires that model … 相似文献
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认知无线电是指能够感知周围频谱环境并动态使用频谱资源的智能无线通信系统。认知无线电的多目标优化问题是一个典型的动态参数优化问题。以传输能量、数据率以及误比特率等多个参数为目标,采用一种基于DNA计算的非支配排序多目标遗传算法(DNA-GA)来对其进行优化。将CR可调参数进行编码作为染色体,产生大小为N的初始化种群,并根据CR目标函数计算个体适应度,再结合克隆操作使算法收敛于全局最优,最终得到CR系统的最优操作参数。仿真结果表明,DNA-GA可以在不同用户需求情况下获得较好的性能优化。 相似文献
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In order to classify the alertness status, 19 channels of electroencephalogram（EEG） signals from 5 subjects were acquired during daytime nap. Ten different types of features（including time domain features, frequency domain features and nonlinear features） were extracted from EEG signals, and an improved self-organizing map（ISOM） neuron network was proposed, which successfully identify three different brain status of the subjects： awareness, drowsiness and sleep. Compared with traditional SOM, the experiment results show that the ISOM generates much better classification accuracy, reaching as high as 89.59%. 相似文献
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1 Introduction Support vector machine (SVM) is a powerful ma-chine learning tool capable of representing non-linearrelationships and producing models that generalizeswell to unseen data .SVMhave been applied widelyinmany fields[1]such as hand-written character recogni-tion ,text categorization,computer vision,speechrec-ognition and gene classification,etc. Despite this , using an SVM requires a certainamount of model selection,i.e.,selection of the ac-tual kernel and its parameters .In rec… 相似文献
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为了精确评估个体心理负荷状态,需要获取目标脑电信号数据,脑电信号是评估脑力负荷变化的重要指标。机器学习和神经网络越来越多地用于脑力负荷分类。利用脑电信号特征可在时域和频域中提取突出信息。因此提出一个结合支持向量机（SVM）与超限学习机（ELM）的混合型脑力负荷分类框架。其中支持向量机作为成员分类器,可在高维EEG特征中查找隐藏信息|超限学习机用于融合成员分类器的输出。将ELM-SVM模型与经典脑力负荷分类器进行比较,得出该模型训练精度准确率为1,且测试精度提升0.1个百分点。 相似文献
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Hong Jiao Akihito Kamata Shudong Wang Ying Jin 《Journal of Educational Measurement》2012,49(1):82-100
The applications of item response theory (IRT) models assume local item independence and that examinees are independent of each other. When a representative sample for psychometric analysis is selected using a cluster sampling method in a testlet‐based assessment, both local item dependence and local person dependence are likely to be induced. This study proposed a four‐level IRT model to simultaneously account for dual local dependence due to item clustering and person clustering. Model parameter estimation was explored using the Markov Chain Monte Carlo method. Model parameter recovery was evaluated in a simulation study in comparison with three other related models: the Rasch model, the Rasch testlet model, and the three‐level Rasch model for person clustering. In general, the proposed model recovered the item difficulty and person ability parameters with the least total error. The bias in both item and person parameter estimation was not affected but the standard error (SE) was affected. In some simulation conditions, the difference in classification accuracy between models could go up to 11%. The illustration using the real data generally supported model performance observed in the simulation study. 相似文献
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T. C. Oshima 《Journal of Educational Measurement》1994,31(3):200-219
There is a paucity of research in item response theory (IRT) examining the consequences of violating the implicit assumption of nonspeededness. In this study, test data were simulated systematically under various speeded conditions. The three factors considered in relation to speededness were proportion of test not reached (5%, 10%, and 15%), response to not reached (blank vs. random response), and item ordering (random vs. easy to hard). The effects of these factors on parameter estimation were then examined by comparing the item and ability parameter estimates with the known true parameters. Results indicated that the ability estimation was least affected by speededness in terms of the correlation between true and estimated ability parameters. On the other hand, substantial effects of speededness were observed among item parameter estimates. Recommendations for minimizing the effects of speededness are discussed 相似文献
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Many computerized testing algorithms require the fitting of some item response theory (IRT) model to examinees' responses to facilitate item selection, the determination of test stopping rules, and classification decisions. Some IRT models are thought to be particularly useful for small volume certification programs that wish to make the transition to computerized adaptive testing (CAT). The one-parameter logistic model (1-PLM) is usually assumed to require a smaller sample size than the three-parameter logistic model (3-PLM) for item parameter calibrations. This study examined the effects of model misspecification on the precision of the decisions made using the sequential probability ratio test (SPRT). For this comparison, the 1-PLM was used to estimate item parameters, even though the items' characteristics were represented by a 3-PLM. Results demonstrated that the 1-PLM produced considerably more decision errors under simulation conditions similar to a real testing environment, compared to the true model and to a fixed-form standard reference set of items. 相似文献
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《Educational Assessment》2013,18(4):317-340
A number of methods for scoring tests with selected-response (SR) and constructed-response (CR) items are available. The selection of a method depends on the requirements of the program, the particular psychometric model and assumptions employed in the analysis of item and score data, and how scores are to be used. This article compares 3 methods: unweighted raw scores, Item Response Theory pattern scores, and weighted raw scores. Student score data from large-scale end-of-course high school tests in Biology and English were used in the comparisons. In the weighted raw score method evaluated in this study, the CR items were weighted so that SR and CR items contributed the same number of points toward the total score. The scoring methods were compared for the total group and for subgroups of students in terms of the resultant scaled score distributions, standard errors of measurement, and proficiency-level classifications. For most of the student ability distribution, the three scoring methods yielded similar results. Some differences in results are noted. Issues to be considered when selecting a scoring method are discussed. 相似文献
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Effect of the scale of quantitative trait data on the representativeness of a cotton germplasm sub-core collection 总被引：1，自引：0，他引：1
Jian-cheng WANG Jin HU Ya-jing GUAN Yan-fang ZHU 《Journal of Zhejiang University. Science. B》2013,14(2):162-170
A cotton germplasm collection with data for 20 quantitative traits was used to investigate the effect of the scale of quantitative trait data on the representativeness of plant sub-core collections.The relationship between the representativeness of a sub-core collection and two influencing factors,the number of traits and the sampling percentage,was studied.A mixed linear model approach was used to eliminate environmental errors and predict genotypic values of accessions.Sub-core collections were constructed using a least distance stepwise sampling(LDSS) method combining standardized Euclidean distance and an unweighted pair-group method with arithmetic means(UPGMA) cluster method.The mean difference percentage(MD),variance difference percentage(VD),coincidence rate of range(CR),and variable rate of coefficient of variation(VR) served as evaluation parameters.Monte Carlo simulation was conducted to study the relationship among the number of traits,the sampling percentage,and the four evaluation parameters.The results showed that the representativeness of a sub-core collection was affected greatly by the number of traits and the sampling percentage,and that these two influencing factors were closely connected.Increasing the number of traits improved the representativeness of a sub-core collection when the data of genotypic values were used.The change in the genetic diversity of sub-core collections with different sampling percentages showed a linear tendency when the number of traits was small,and a logarithmic tendency when the number of traits was large.However,the change in the genetic diversity of sub-core collections with different numbers of traits always showed a strong logarithmic tendency when the sampling percentage was changing.A CR threshold method based on Monte Carlo simulation is proposed to determine the rational number of traits for a relevant sampling percentage of a sub-core collection. 相似文献
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Recently, advancements in Bayesian structural equation modeling (SEM), particularly software developments, have allowed researchers to more easily employ it in data analysis. With the potential for greater use, come opportunities to apply Bayesian SEM in a wider array of situations, including for small sample size problems. Effective use of Bayseian estimation hinges on selection of appropriate prior distributions for model parameters. Researchers have suggested that informative priors may be useful with small samples, presuming that the mean of the prior is accurate with respect to the population mean. The purpose of this simulation study was to examine model parameter estimation for the Multiple Indicator Multiple Cause model when an informative prior distribution had an incorrect mean. Results demonstrated that the use of incorrect informative priors with somewhat larger variance than is typical, yields more accurate parameter estimates than do naïve priors, or maximum likelihood estimation. Implications for practice are discussed. 相似文献