999 resultados para Programa PCA
Resumo:
Abarca los trabajos que se presentan durante los 3 días que dura el evento infantil.
Resumo:
The fish smoking is a traditional process in most african countries and has been gradually improved to the light of changes in forms, techniques and materials. In Mozambique, in particular, this method is not as developed as expected, because it has more advantages in wetlands during rainy seasons, where there is no shortage of salt and in order to give a special taste to the dry fish. In many parts of the country, mainly in coastal areas, the smoking process is made manually by families: a small fire with any type of wood, close to a small amount of fish on a stick, tilted on fire in order to take smoke and heat for several hours. This process is used in the south (Inhaca Island), in central and northern regions (Beira, Nampula) and was also seen in Niassa Lake. This paper presents a program aimed at the application of existing knowledge about fish smoking process and at technology improvement.
Resumo:
就主量分析(PCA)的基本原理、 运用发展过程及在动物分类学上的应用作了 阐明。并以亚洲疣猴类5个属为例, 利用其面颅和颅骨的6项变量进行分析, 且 叙述了PCA的主要计算过程。 结果表明, 在分类过程中, 主要是面颅的凸度和宽 度结构起贡献作用。图5参21
Resumo:
以氯代苯胺(PCA)为选择基质,用驯化技术从降解对二氯苯(pDCB)的富集培养物中得到了以同化PCA为唯一碳源和氮源的混合微生物.将这种固定在填充床反应器中的微生物用于PCA的降解作用研究中.在该反应器里,PCA的生物降解遵循Logistic方程q=qmax/(1+eα-βUv).由方程求出了主要的动力学常数,Ks(半速率常数)和qmax(最大比基质降解速率).于PCA降解的同时,释放氯离子到培养基中.在水力停留时间3h,进水PCA浓度为360mg·L-1情况下,基质的体积降解率达到125mg·L-1
Resumo:
An algorithm of PCA face recognition based on Multi-degree of Freedom Neurons theory is proposed, which based on the sample sets' topological character in the feature space which is different from "classification". Compare with the traditional PCA+NN algorithm, experiments prove its efficiency.
Resumo:
提出主元分析PCA(Principal Component Analysis)用于语音检测的方法研究.用主元分析法在多维空间中建立坐标轴,将待处理信号投影到该坐标轴中,通过分析投影结果判断是否为语音信号.通过将语音和非语音分别建立子空间,来区分语音和非语音信号.该方法不同于常规的语音时域、频域处理方法,而是在多维空间中对信号进行分析·实验结果表明,该方法准确率高、简单、容易实现,而且能区分多种非语音信号.
Resumo:
本文提出了一种基于仿生模式识别和PCA/ICA的DOA估计方法.这种方法的建模过程是用在实际环境下采集的训练样本构造人工神经网络模型,对环境的适应能力较强;且这种方法采用PCA/ICA进行特征提取,使数据得到有效压缩,可以实现系统实时处理.实验结果表明:在信噪比为20dB和0dB时,该方法的正确估计率可达100%;在信噪比降为-20dB时,该方法仍有83%的可识别率.
Resumo:
在多源遥感影像融合中,基于传统PCA变换的多源遥感影像融合的光谱分辨率受到较大影响。提出了一种新的基于PCA变换的多源遥感影像像素级融合方法,通过在传统PCA变换融合算法基础上引入小波变换融合,保留了多波段遥感图像光谱特性的有用信息,进一步提高融合后遥感影像的效果。给出实验的融合结果,并与传统PCA变换方法进行对比,证明了该方法的有效性。