音乐与物理

从音乐是一种声波出发，从物理上介绍了音乐物理学－音乐声的产生、接收传播，它的性质及其他物质的相互作用。从音乐声的物理基础成分频率，声强和时值及其对应的主观量出发，构成了音色、旋律、节奏和声等音乐和诸要素。说明了音律学，和声的协和性，乐器的分类、结构、振动模式，歌唱中的物理、音乐表演中的物理，音乐电声中的物理问题，室内音乐声的传播以及研究音乐的物理方法等。     

高超声速低温喷管副喷管参数化设计

 通过对DF化学激光器高超声速低温(HYLTE)喷管副喷管流动与几何参数进行制约关系和敏感性分析，确定了能够对副喷管进行参数化设计的4个基本几何控制参数和2个调节参数，初步建立了HYLTE喷管副喷管的参数化设计方法。引入了相对未混合度作为衡量喷管混合效果的性能参数，建立了较完备的3维反应流数值模拟计算程序。结果表明：该方法选择的基本参数能够敏感地反映HYLTE喷管副喷管的尺寸特征和关键性能。     

考虑中子泄漏修正的快堆蒙特卡罗少群截面参数制作与验证方法

一种基于B1均匀化方程的泄漏修正模型在连续能量蒙特卡罗程序TRIPOLI4中得以实现并且用于制作少群截面参数。此蒙卡泄漏修正模型通过在连续能量的蒙卡模拟以及求解B1均匀化方程之间迭代,最终得到蒙卡模拟下的临界状态。通过此方法得到的少群截面参数较其他蒙卡以及确定论方法有两点显著优势:用于求解B1均匀化方程的少群常数是用通过临界状态的通量谱得到的;考虑了泄漏效应的蒙卡模拟可以更真实地反映组件计算时的能谱状态。为验证此泄漏修正模型,一个由连续能量的TRIPOLI4模拟而得到的数值临界实验被用于分析与比较。通过与其他蒙卡程序SERPENT以及确定论程序ECCO进行结果对比,可证明此B1泄漏修正方法能够给出更精确的用于堆芯计算的少群截面参数。     

水冷包层试验段设计与流动特性研究

针对水冷包层子模块并行通道的流量分配对热量导出的影响,以水冷包层子模块第一壁为研究对象,对其并行通道试验段的模化设计与流量分配特性展开了研究。采用模化方法对第一壁的结构进行设计,得出试验段相关参数。采用计算流体力学(CFD)的方法对模化设计的试验段进行数值模拟,并分析其流动状态。将结果与原型结构下的流动特性参数进行比较,验证了采用模化方法得到的试验段参数可以有效反映水冷包层子模块第一壁的流动特点,为试验装置的搭建提供参考。     

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针对水冷包层子模块并行通道的流量分配对热量导出的影响,以水冷包层子模块第一壁为研究对象,对其并行通道试验段的模化设计与流量分配特性展开了研究。采用模化方法对第一壁的结构进行设计,得出试验段相关参数。采用计算流体力学(CFD)的方法对模化设计的试验段进行数值模拟,并分析其流动状态。将结果与原型结构下的流动特性参数进行比较,验证了采用模化方法得到的试验段参数可以有效反映水冷包层子模块第一壁的流动特点,为试验装置的搭建提供参考。     

考虑几何不确定性的翼型随机参数化方法研究

参数化方法是翼型设计的重要方法。在翼型设计阶段,参数化模型中的变量通常认为在一定区间内变化,并进行离散化。参数化模型的变量较多时,设计样本空间大,计算量大。本文提出一种翼型的随机参数化设计方法,采用类/形函数变换方法参数化翼型,参数化模型的变量为服从一定概率分布的随机变量,基于不确定性量化方法与CFD模拟获得翼型气动性能的统计特性。将此方法与OpenFOAM耦合,对S809翼型进行了随机参数化建模,比较了蒙特卡洛、拉丁超立方和基于稀疏网格的多项式混沌法与CFD结合的精度和效率。结果表明基于稀疏网格的多项式混沌法收敛速度快和精度高,可以大幅减小高维设计变量下的计算量;通过敏感性分析寻找了影响翼型气动性能的主要设计变量。     

各向异性扩散滤波的正则化参数选取方法

研究了图像处理中各向异性扩散的正则化参数选取问题.根据分片常数模型，提出了一种噪声估计方法，该方法通过寻找图像中的最小区域方差来估计噪声;分析了正则化参数与图像噪声的关系，提出了一个正则化参数选取的修正公式，该公式使正则化参数能根据图像噪声自适应调整;最后给出了由正则化参数选取高斯模板尺度的规则.实验结果显示，这种正则化选取方法可以使各向异性扩散方程对图像噪声具有很好的自适应性.     

改进的固定点图像复原算法（英文）

研究了周期边界条件下,Tikhonov正则化的固定点算法,提出了变化正则化参数的方法。首先对正则化参数取较大值,抑制复原图像中的噪声,通过得出的收敛结果来修正初始梯度;然后对正则化参数取较小值,以增强复原图像中的细节。实验结果表明,与当前求解L1范数正则化函数和全变分正则化函数的流行算法比较,本文算法对于运动模糊与高斯模糊图像的复原效果更佳。     

结合区分性训练深度神经网络的歌声与伴奏分离方法

针对音乐信号中的歌声与伴奏相互关联难以分离的问题,提出了一种区分性训练深度神经网络(Deep Neural Network,DNN)的音乐分离方法。首先,在DNN模型的基础上同时考虑歌声与伴奏间的重建误差和区分性信息,提出了一种改进的目标函数进行区分性训练;其次,在DNN模型上额外添加一层,引入时频掩蔽对估计出的歌声伴奏进行联合优化,相应的时域信号由傅里叶逆变换获得;最后,验证不同参数设置对分离性能的影响,并与现有的音乐分离方法进行对比.实验结果表明,改进的目标函数和时频掩蔽的引入明显提高了DNN的分离性能,且与现有的音乐分离方法相比分离性能最高提高了4 dB从而证实所提方法是一种有效的音乐分离方法。      

基于全叶片曲面参数化方法的涡轮气动优化

为进一步挖掘涡轮性能潜力,实现气动优化参数化降维,减少优化耗时,基于全叶片贝塞尔曲面参数化方法、多岛遗传算法和CFD求解器构建了涡轮三维优化平台。通过建立涡轮叶片吸压力面展开曲面和贝塞尔曲面的参数化映射,全叶片贝塞尔曲面参数化方法实现了叶片吸力面和压力面的同时变形控制,减少了优化控制变量,具有型面光顺性和构造便捷性。对TTM跨音涡轮开展全局气动优化设计研究,结果表明：优化历时约70 h,涡轮设计点绝热效率提升0.48个百分点,流量增加0.97%,膨胀比下降0.32%,验证了曲面参数化优化方法对涡轮气动优化问题的有效性、工程实用性和降维特性。     

Computational models of music perception and cognition I: The perceptual and cognitive processing chain

We present a review on perception and cognition models designed for or applicable to music. An emphasis is put on computational implementations. We include findings from different disciplines: neuroscience, psychology, cognitive science, artificial intelligence, and musicology. The article summarizes the methodology that these disciplines use to approach the phenomena of music understanding, the localization of musical processes in the brain, and the flow of cognitive operations involved in turning physical signals into musical symbols, going from the transducers to the memory systems of the brain. We discuss formal models developed to emulate, explain and predict phenomena involved in early auditory processing, pitch processing, grouping, source separation, and music structure computation. We cover generic computational architectures of attention, memory, and expectation that can be instantiated and tuned to deal with specific musical phenomena. Criteria for the evaluation of such models are presented and discussed. Thereby, we lay out the general framework that provides the basis for the discussion of domain-specific music models in Part II.     

基于音色单元分布的音乐结构分析

音乐的结构是音乐作品表达作者思想的一种重要形式,也是听众理解音乐作品内涵的有效途径。本文研究了基于音乐特征的音色单元建模方法,研究了在Fisher准则下,根据局部范围音色单元的分布,采用非监督聚类方法分析音乐的结构。实验结果证明了基于离散余弦变换的音色特征,用音色单元分布聚类算法进行音乐结构分析的有效性。      

融合声源分离及反复结构模型的音乐分离方法

针对现有的单一音乐分离算法难以分离背景音乐和歌声的问题,提出一种融合声源分离及反复结构模型的音乐分离方法。该方法首先通过迭代的方式分离出音乐的谐波声源和冲击声源,再引入节奏谱分析不同声源的能量谱矩阵,对其建立反复周期结构模型,最后保留谐波源的反复周期成分,去除冲击源的反复周期成分,得到分离后的背景音乐和歌声。针对MIR-1K数据库,对1000首音乐片段的分离实验表明,与现有分离方法对比,本文方法在分离背景音乐和歌声时均表现出优异的性能。      

Pitch discrimination abilities in classical Arab-music listeners

The current experiment examined pitch discrimination thresholds in listeners of classical Arab music, and listeners of Western popular music. Classical Arab music is characterized by modes (“Maqamat”, plural of “Maqam” in Arabic language) of which the smallest interval is a quarter tone. In contrast, the smallest interval in Western music is a semitone. We hypothesized that daily exposure to a musical style involving minuscule pitch differences may have a positive effect on pitch discrimination abilities. Results demonstrate superior pitch discrimination abilities in the classical Arab music listeners. These results indicate that musical cultures may differ in their influence on perceptual abilities, depending on their basic acoustic characteristics.     

An investigation into the linear and nonlinear correlation of two music walk sequences

In order to investigate the features of a multiple-part musical score which enhance its appeal to the listener’s ear, this study performs a robust analysis of the correlation between two musical sequences. In the proposed approach, a series of notes are extracted from seven well-known classical pieces of music and are converted into one-variable “music walks”. The linear correlation between pairs of music walks is assessed using the conventional linear correlation coefficient, while the nonlinear correlation is examined using the mutual information concept. The results show that even though two musical time walks may exhibit virtually no linear correlation, they invariably have a certain degree of nonlinear correlation. In other words, to truly understand the correlation between two musical sequences, it is necessary to consider not only the linear correlation between them, but also the nonlinear correlation. In addition, it is shown that the normalized mutual information coefficient between musical sequences has a relatively low value and varies significantly over the course of the musical score. Thus, it can be inferred that the appeal of a musical score stems at least in part from significant variations in both the melody and the rhythm of the constituent parts such that the overall score has a rich and unpredictable property.     

Pitch-interval discrimination and musical expertise: Is the semitone a perceptual boundary?

The ability to discriminate pitch changes (or intervals) is foundational for speech and music. In an auditory psychophysical experiment, musicians and non-musicians were tested with fixed- and roving-pitch discrimination tasks to investigate the effects of musical expertise on interval discrimination. The tasks were administered parametrically to assess performance across varying pitch distances between intervals. Both groups showed improvements in fixed-pitch interval discrimination as a function of increasing interval difference. Only musicians showed better roving-pitch interval discrimination as interval differences increased, suggesting that this task was too demanding for non-musicians. Musicians had better interval discrimination than non-musicians across most interval differences in both tasks. Interestingly, musicians exhibited improved interval discrimination starting at interval differences of 100 cents (a semitone in Western music), whereas non-musicians showed enhanced discrimination at interval differences exceeding 125 cents. Although exposure to Western music and speech may help establish a basic interval-discrimination threshold between 100 and 200 cents (intervals that occur often in Western languages and music), musical training presumably enhances auditory processing and reduces this threshold to a semitone. As musical expertise does not decrease this threshold beyond 100 cents, the semitone may represent a musical training-induced intervallic limit to acoustic processing.     

Computational models of music perception and cognition II: Domain-specific music processing

In Part I [Purwins H, Herrera P, Grachten M, Hazan A, Marxer R, Serra X. Computational models of music perception and cognition I: The perceptual and cognitive processing chain. Physics of Life Reviews 2008, in press, doi:10.1016/j.plrev.2008.03.004], we addressed the study of cognitive processes that underlie auditory perception of music, and their neural correlates. The aim of the present paper is to summarize empirical findings from music cognition research that are relevant to three prominent music theoretic domains: rhythm, melody, and tonality. Attention is paid to how cognitive processes like category formation, stimulus grouping, and expectation can account for the music theoretic key concepts in these domains, such as beat, meter, voice, consonance. We give an overview of computational models that have been proposed in the literature for a variety of music processing tasks related to rhythm, melody, and tonality. Although the present state-of-the-art in computational modeling of music cognition definitely provides valuable resources for testing specific hypotheses and theories, we observe the need for models that integrate the various aspects of music perception and cognition into a single framework. Such models should be able to account for aspects that until now have only rarely been addressed in computational models of music cognition, like the active nature of perception and the development of cognitive capacities from infancy to adulthood.     

Fusion research and international scientific collaboration

Physics and technology have played a major role in shaping the development, performance, interpretation and composition of music for many centuries. From the twentieth century, electronics and communications have provided recording and broadcasting that gives access to worldwide music and performers of many musical genres. Early scientific influence came via improved or totally new instruments, plus larger and better concert halls. Instrument examples range from developments of violins or pianos to keyed and valved wood wind and brass that offer chromatic performance. New sounds appeared by inventions of totally new instruments, such as the saxophone or the Theremin, to all the modern electronic influence on keyboards and synthesisers. Electronic variants of guitars are effectively new instruments that have spawned totally original musical styles. All such advances have encouraged more virtuosic performance, larger halls, a wider range of audiences and a consequent demand and ability of composers to meet the new challenges. Despite this immense impact, the role of physics and technology over the last few centuries has mostly been ignored, although it was often greater than any links to arts or culture. Recorded and broadcast music has enhanced our expectations on performance and opened gateways to purely electronically generated sounds, of the now familiar electronic keyboards and synthesisers. This brief review traces some of the highlights in musical evolution that were enabled by physics and technology and their impact on the musical scene. The pattern from the past is clear, and so some of the probable advances in the very near future are also predicted. Many are significant as they will impinge on our appreciation of both current and past music, as well as compositional styles. Mention is made of the difference in sound between live and recorded music and the reasons why none of us ever have precisely the same musical experience twice, even from the same recording. Similarly, it is impossible to appreciate earlier music from the same perspective as occurred when it was first composed and performed, or indeed from later interpretations.     

Musical emotions: Functions,origins, evolution

Theories of music origins and the role of musical emotions in the mind are reviewed. Most existing theories contradict each other, and cannot explain mechanisms or roles of musical emotions in workings of the mind, nor evolutionary reasons for music origins. Music seems to be an enigma. Nevertheless, a synthesis of cognitive science and mathematical models of the mind has been proposed describing a fundamental role of music in the functioning and evolution of the mind, consciousness, and cultures. The review considers ancient theories of music as well as contemporary theories advanced by leading authors in this field. It addresses one hypothesis that promises to unify the field and proposes a theory of musical origin based on a fundamental role of music in cognition and evolution of consciousness and culture. We consider a split in the vocalizations of proto-humans into two types: one less emotional and more concretely-semantic, evolving into language, and the other preserving emotional connections along with semantic ambiguity, evolving into music. The proposed hypothesis departs from other theories in considering specific mechanisms of the mind–brain, which required the evolution of music parallel with the evolution of cultures and languages. Arguments are reviewed that the evolution of language toward becoming the semantically powerful tool of today required emancipation from emotional encumbrances. The opposite, no less powerful mechanisms required a compensatory evolution of music toward more differentiated and refined emotionality. The need for refined music in the process of cultural evolution is grounded in fundamental mechanisms of the mind. This is why today's human mind and cultures cannot exist without today's music. The reviewed hypothesis gives a basis for future analysis of why different evolutionary paths of languages were paralleled by different evolutionary paths of music. Approaches toward experimental verification of this hypothesis in psychological and neuroimaging research are reviewed.     

A structurally guided method for the decomposition of expression in music performance

A method for separating, profiling, and quantifying the contributions of different structural components to expressive musical performance is described. The method is demonstrated through its application to a set of expert piano performances of a short piece from the classical period. The results show that the output of the method aids in the understanding of how the different structural components in a piece of music combine in the generation of an expressive performance. A second demonstration applies the method to performances at different tempi to illustrate its effectiveness in pinpointing the structural features responsible for small but statistically significant differences between performances. The method is compared with other approaches to the analysis and modeling of musical performance, and a number of potential applications are identified.