What songbirds teach us about learning

Bird fanciers have known for centuries that songbirds learn their songs. This learning has striking parallels to speech acquisition: like humans, birds must hear the sounds of adults during a sensitive period, and must hear their own voice while learning to vocalize. With the discovery and investigation of discrete brain structures required for singing, songbirds are now providing insights into neural mechanisms of learning. Aided by a wealth of behavioural observations and species diversity, studies in songbirds are addressing such basic issues in neuroscience as perceptual and sensorimotor learning, developmental regulation of plasticity, and the control and function of adult neurogenesis.     

Perceptual learning of dot pattern

Dot pattern is a type of pattern defined by specific spatial relationship among some dots. As a compensation for concrete and meaningful visual stimuli, meaningless dot pattern can be used as stimuli in learning tasks. We performed an experiment for exploring the perceptual learning process of dot pattern against random-dot background. Participants were required to learn two types of dot patterns (9-dot and 11-dot). They were assigned to two groups: participants in Group 1 learned 9-dot pattern first and 11-dot pattern later, while those in Group 2 learned 11-dot pattern first and 9-dot pattern later. The results showed that participants could acquire the spatial relationship of dot pattern through perceptual learning in relatively short learning time. In comparison with 9-dot pattern, learning time of 11-dot pattern was slightly longer and its accuracy rate lower, but there was significant positive transfer effect from 11-dot pattern learning to 9-dot learning.     

Perceptual learning of dot pattern

Dot pattern is a type of pattern defined by specific spatial relationship among some dots. As a compensation for concrete and meaningful visual stimuli, meaningless dot pattern can be used as stimuli in learning tasks. We performed an experiment for exploring the perceptual learning process of dot pattern against random-dot background. Participants were required to learn two types of dot patterns (9-dot and 11-dot). They were assigned to two groups: participants in Group 1 learned 9-dot pattern first and 11-dot pattern later, while those in Group 2 learned 11-dot pattern first and 9-dot pattern later. The results showed that participants could acquire the spatial relationship of dot pattern through perceptual learning in relatively short learning time. In comparison with 9-dot pattern, learning time of 11-dot pattern was slightly longer and its accuracy rate lower, but there was significant positive transfer effect from 11-dot pattern learning to 9-dot learning.     

用递归BDD(二元决策图)技术分析因果图

故障树是以系统最不希望发生的顶事件为目标,通过分析找出导致顶上事件发生的全部因素;在故障树分析中,二元决策图(简称BDD)是最有效的方法之一,由于故障树和因果图都是用图形表示因果关系,两者具有很多相似性,而BDD在故障树中有广泛的应用;通过研究表明:在一定条件下,故障树和因果图之间可以互相转化,因此可以分析BDD的原理,并将BDD技术用来分析因果图。     

ZENK基因与鸣禽鸣啭行为

雄性鸣禽的鸣转行为能诱发ZENK在相关脑区的表达,但鸣转方式（求偶性鸣转或非求偶性鸣转）的不同会导致ZENK基因活性的差异,鸟脑内ZENK基因的研究,为深入探讨动物行为与脑活动这间的相关性提供了依据。     

一种递推的Kantorovich型算子的逼近

构造出一种递推的Kantorovich型算子,利用算子分解技巧研究了其在经典空间上的收敛性和逼近特征,并给出更加精细的渐进展式以及逼近度估计.     

基于网络的地理研究性学习实施与评价

对网络技术环境下进行地理研究性学习的教学模式、实施方案及评价内容做初步探索，以构建一个适应信息时代的教学新体系。     

The evolution of syntactic communication

Animal communication is typically non-syntactic, which means that signals refer to whole situations. Human language is syntactic, and signals consist of discrete components that have their own meanings. Syntax is a prerequisite for taking advantage of combinatorics, that is, "making infinite use of finite means. The vast expressive power of human language would be impossible without syntax, and the transition from non-syntactic to syntactic communication was an essential step in the evolution of human language. We aim to understand the evolutionary dynamics of this transition and to analyse how natural selection can guide it. Here we present a model for the population dynamics of language evolution, define the basic reproductive ratio of words and calculate the maximum size of a lexicon. Syntax allows larger repertoires and the possibility to formulate messages that have not been learned beforehand. Nevertheless, according to our model natural selection can only favour the emergence of syntax if the number of required signals exceeds a threshold value. This result might explain why only humans evolved syntactic communication and hence complex language.     

Change in pattern of ongoing cortical activity with auditory category learning

Humans are able to classify novel items correctly by category; some other animals have also been shown to do this. During category learning, humans group perceptual stimuli by abstracting qualities from similarity relationships of their physical properties. Forming categories is fundamental to cognition and can be independent of a 'memory store' of information about the items or a prototype. The neurophysiological mechanisms underlying the formation of categories are unknown. Using an animal model of category learning, in which frequency-modulated tones are distinguished into the categories of 'rising' and 'falling' modulation, we demonstrate here that the sorting of stimuli into these categories emerges as a sudden change in an animal's learning strategy. Electro-corticographical recording from the auditory cortex shows that the transition is accompanied by a change in the dynamics of cortical stimulus representation. We suggest that this dynamic change represents a mechanism underlying the recognition of the abstract quality (or qualities) that defines the categories.     

基于模糊模式识别算法的学习型红外遥控器的编码压缩

介绍一种自学习型红外遥控器的设计方法.该红外遥控器采用测量脉冲宽度的原理,通过模糊算法识别遥控信号实现自学习功能,最后对数据进行压缩,提高了存储效率.该装置可以代替各种不同的遥控器控制家用电器.     

K方体的递归构造

本文给出了k方体递归的构造性定义,并使用构造方法解决了V.V.Firsov(1965)提出的表征k方体中可嵌入图的问题(见[1]).     

递归定义与归纳证法

递归定义与归纳证法是数学中最基本、最原始的手段,它不象一般人所认为的那样只是自然数所特有的。本文通过揭示递归定义与归纳证法的实质表明它们是本质上不依赖于自然数的逻辑系统内的特征,因而也适用于许多非自然数的对象。     

递归程序的复杂性问题

递归是一种程序设计方法。递归算法能将很复杂的问题用十分简洁的形式加以表达。然而递归程序的复杂性很高,所以通常光用递归程序描述问题,然后设法变换为效率较高的程序。本文给出计算递归程序复杂性的公式,并讨论了降低递归程序复杂性的几种方法。     

有色噪声干扰系统的参数辨识递推算法

为了辨识受有色噪声干扰的系统参数,提出一种递推算法。该算法由系统部分的参数估计和噪声部分的参数估计2部分组成。系统参数估计采用的是包含当前预报误差和之前估计误差的递推算法辨识。噪声部分参数则是采用扩展的最小二乘算法辨识。该文对新的递推算法进行了仿真,实验结果显示该算法能够降低噪声对参数估计的影响,减小估计误差,较精确地辨识出受有色噪声干扰系统的参数。     

论多媒体与合作学习相结合的生物学双语教学模式

多媒体与合作学习相结合的教学模式是在双语教学实践中探索出的一种将现代多媒体教学手段与先进的合作学习理论策略相结合的双语教学模式.它既能发挥多媒体技术在生物学双语教学中的独特优势,又将合作学习的先进理念贯穿于整个教学过程,有利于激发学生对双语教学的学习热情,提高双语教学的效果.它通过师生之间、学生之间的互动教学与合作学习,形成一种合作化、人性化的教学环境,以促进学生的全面发展.     

有色噪声干扰系统的参数辨识递推算法

为了辨识受有色噪声干扰的系统参数,提出一种递推算法。该算法由系统部分的参数估计和噪声部分的参数估计2部分组成。系统参数估计采用的是包含当前预报误差和之前估计误差的递推算法辨识。噪声部分参数则是采用扩展的最小二乘算法辨识。该文对新的递推算法进行了仿真,实验结果显示该算法能够降低噪声对参数估计的影响,减小估计误差,较精确地辨识出受有色噪声干扰系统的参数。     

等维灰数递补动态预测

本文提出一种等维灰数递补动态预测技术。通过对所获信息的不断有效利用,将灰色动态GM(1,1)模型中灰参数逐次加以修正,使模型不断得到改进,从而提高了预测精度。应用实例表明,用本预测技术可取得较满意的结果。     

论多媒体与合作学习相结合的生物学双语教学模式

多媒体与合作学习相结合的教学模式是在双语教学实践中探索出的一种将现代多媒体教学手段与先进的合作学习理论策略相结合的双语教学模式。它既能发挥多媒体技术在生物学双语教学中的独特优势,又将合作学习的先进理念贯穿于整个教学过程,有利于激发学生对双语教学的学习热情,提高双语教学的效果。它通过师生之间、学生之间的互动教学与合作学习,形成一种合作化、人性化的教学环境,以促进学生的全面发展。     

非线性系统的递推设计

对非线性系统的递推设计方法进行综述，包括反演设计、前推设计和交替设计，对该类方法的某些重要的概念和思想进行了阐述，指出了未来的主要研究方向，期望对这一领域的理论和应用研究有一定的辅助作用。