学科质量评价的属性识别法

高等学校学科建设是体现办学实力和办学特色的 基础性工作。因此，建立合理的学科质量评价体系，从 而对高校学科质量进行评价，对提高高校教学质量、科 研水平以及社会服务能力等方面具有重要意义。属性 识别理论已成功地应用于环境质量等多属性综合评价 领域，取得了较好的评     

基于嵌入式平台的数字模糊识别技术的实现

在嵌入式开发平台上实现具有图形用户界面(GUI)的模糊模式数字识别系统.使用嵌入式操作系统uCOSⅡ编程接口实现系统的多任务特性与任务间的通信;通过改进开发板附带的触摸屏接口函数实现手写输入;基于模糊数学的基本理论与方法,使用模糊模式识别技术分析手写输入的数据.在嵌入式开发平台上完成了一套实验性的支持手写输入的用户图形界面系统,该系统可以接受和处理用户通过键盘或者触摸屏输入的信息.实验结果表明,采用2种模糊识别技术相结合的嵌入式手写输入系统能在降低系统硬件配置的同时保持较高的识别率.     

邓小平的价值认识论刍议

邓小平提出的“猫论”是一种全新的马克思主义价值认识论,它体现了求真认识和价值认识的统一,为我们观察、研究事物开辟了一个新的视角,它是邓小平认识论的灵魂,是邓小平理论的实质。对于社会主义现代化建设具有普遍的方法论意义。     

基于Python语言的模式识别应用

以模式识别中英文文字识别和人脸检测为例,利用PIL库、pytesser库和OpenCV库实现了图像灰度转换、降噪处理、文字识别和目标检测。应用表明,Python处理实验数据的方法简便灵活,表征数据图形直观明了,适合在数字图像处理课程的模式识别章节中应用。     

Clinical detection and movement recognition of neuro signals

INTRODUCTION Human limbs are complex, delicate systems.Their reconstruction, both for appearance and forfunction compensations, proves to be complicatedprojects. With the development of science and tech-nology, both researchers and disabilities hope to haveartificial limb much more perky, comfortable, dex-terous and effective. Although thousands of pros-thetic limbs are commercially available worldwide,most of them, from mechanical styles to electricstyles, from motion controlled t…     

浅谈中学生数学焦虑的成因和对策

引起中学生数学焦虑的因素主要有知识、观念技能与能力等认知体验因素及家庭、教师学习者等情感体验因素。改善学生数学学习的途径有帮助学生剖析焦虑根源,使用技术暗示及鼓励合作等。     

卡克鲁理论研究范式下的世界英语变体分析

文章旨在运用语言学家卡克鲁的三大同轴圈理论及其研究范式分析世界英语的类别和特征,并基于其语言变体的标准化和本土化特征,探究世界英语的语言功能和作用,从而客观阐释世界英语对全球交流与合作产生的重大影响。     

基于CAJViewer的学术文献使用技巧

学术文献保存格式除了传统的PDF外,还包括CAJ、KDH、NH、CAA、TEB等格式,CAJViewer作为一款专门的文献浏览软件,通吃这些文献格式,具有浏览页面、查找文字、文本识别、邮件传输等九大功能,可取代AdobeReader阅读器对PDF的浏览功能,也不需要单独使用OCR软件而进行文本识别,灵活使用其功能,可极大地方便用户对学术文献的浏览和使用。     

Extraction of novel features for emotion recognition

Hilbert-Huang transform method has been widely utilized from its inception because of the superiority in varieties of areas. The Hilbert spectrum thus obtained is able to reflect the distribution of the signal energy in a number of scales accurately. In this paper, a novel feature called ECC is proposed via feature extraction of the Hilbert energy spectrum which describes the distribution of the instantaneous energy. The experimental results conspicuously demonstrate that ECC outperforms the traditional short-term average energy. Combination of the ECC with mel frequency cepstral coefficients (MFCC) delineates the distribution of energy in the time domain and frequency domain, and the features of this group achieve a better recognition effect compared with the feature combination of the short-term average energy, pitch and MFCC. Afterwards, further improvements of ECC are developed. TECC is gained by combining ECC with the teager energy operator, and EFCC is obtained by introducing the instantaneous frequency to the energy. In the experiments, seven status of emotion are selected to be recognized and the highest recognition rate 83.57% is achieved within the classification accuracy of boredom reaching 100%. The numerical results indicate that the proposed features ECC, TECC and EFCC can improve the performance of speech emotion recognition substantially.     

基于CFAR的SAR图像分割

选用瑞利分布模型对SAR图像进行恒虚警率(CFAR)检测。提出新的参考窗口选取方法,并针对虚警特点提出新的均值估计方法。实验证明,与一般的均值估计方法相比,文中提出的均值估计方法是可行的、有效的,且与其中提出的参考窗口选取方法相结合能更好地去除虚警,保留目标信息。