Neuroscience (also known as neurobiology) is a science that studies the structure, function, development, pharmacology and pathology of the nervous system. In recent years, C. Cotardo has introduced coding theory into...Neuroscience (also known as neurobiology) is a science that studies the structure, function, development, pharmacology and pathology of the nervous system. In recent years, C. Cotardo has introduced coding theory into neuroscience, proposing the concept of combinatorial neural codes. And it was further studied in depth using algebraic methods by C. Curto. In this paper, we construct a class of combinatorial neural codes with special properties based on classical combinatorial structures such as orthogonal Latin rectangle, disjoint Steiner systems, groupable designs and transversal designs. These neural codes have significant weight distribution properties and large minimum distances, and are thus valuable for potential applications in information representation and neuroscience. This study provides new ideas for the construction method and property analysis of combinatorial neural codes, and enriches the study of algebraic coding theory.展开更多
As a main structure of the limbic system,the hippocampus plays a critical role in pain perception and chronicity.The ventral hippocampal CA1(vCA1)is closely associated with negative emotions such as anxiety,stress,and...As a main structure of the limbic system,the hippocampus plays a critical role in pain perception and chronicity.The ventral hippocampal CA1(vCA1)is closely associated with negative emotions such as anxiety,stress,and fear,yet how vCA1 neurons encode nociceptive information remains unclear.Using in vivo electrophysiological recording,we characterized vCA1 pyramidal neuron subpopulations that exhibited inhibitory or excitatory responses to plantar stimuli and were implicated in encoding stimuli modalities in naïve rats.Functional heterogeneity of the vCA1 pyramidal neurons was further identified in neuropathic pain conditions:the proportion and magnitude of the inhibitory response neurons paralleled mechanical allodynia and contributed to the confounded encoding of innocuous and noxious stimuli,whereas the excitatory response neurons were still instrumental in the discrimination of stimulus properties.Increased theta power and theta-spike coupling in vCA1 correlated with nociceptive behaviors.Optogenetic inhibition of vCA1 pyramidal neurons induced mechanical allodynia in naïve rats,whereas chemogenetic reversal of the overall suppressed vCA1 activity had analgesic effects in rats with neuropathic pain.These results provide direct evidence for the representations of nociceptive information in vCA1.展开更多
By mcans of stable attractors of discret Hopfield neural network (DHNN) , anew class of nonlinear error control codes is sugsested and some relativetheorems are presented. A kind of single error control codes is also ...By mcans of stable attractors of discret Hopfield neural network (DHNN) , anew class of nonlinear error control codes is sugsested and some relativetheorems are presented. A kind of single error control codes is also given forillustrating this new approach.展开更多
Presents the fuzzy neural network optimized by hybrid coded genetic algorithm of decimal encoding and binary encoding, the searching ability and stability of genetic algorithms enhanced by using binary encoding during...Presents the fuzzy neural network optimized by hybrid coded genetic algorithm of decimal encoding and binary encoding, the searching ability and stability of genetic algorithms enhanced by using binary encoding during the crossover operation and decimal encoding during the mutation operation, and the way of accepting new individuals by probability adopted, by which a new individual is accepted and its parent is discarded when its fitness is higher than that of its parent, and a new individual is accepted by probability when its fitness is lower than that of its parent. And concludes with calculations made with an example that these improvements enhance the speed of genetic algorithms to optimize the fuzzy neural network controller.展开更多
A method of assigning binary indexes to codevectors in vector quantization (VQ)system, which is called pseudo-Gray coding, is presented in this paper by constructing a kind of Hopfield neural network. Pseudo-Gray codi...A method of assigning binary indexes to codevectors in vector quantization (VQ)system, which is called pseudo-Gray coding, is presented in this paper by constructing a kind of Hopfield neural network. Pseudo-Gray coding belongs to joint source/channel coding, which could provide a redundancy-free error protection scheme for VQ of analog signals when the binary indexes of signal codevectors are used as channel symbols on a discrete memoryless channel. Since pseudo-Gray coding is of combinatorial optimization problems which are NP-complete problems,globally optimal solutions are generally impossible. Thus, a kind of Hopfield neural network is used by constructing suitable energy function to get sub-optimal solutions. This kind of Hop field neural network is easily modified to solve simplified version of pseudo-Gray coding for single bit-error channel model. Simulating experimental results show that the method introduced here could offer good performances.展开更多
A new 3D surface contouring and ranging system based on digital fringe projection and phase shifting technique is presented. Using the phase-shift technique, points cloud with high spatial resolution and limited accur...A new 3D surface contouring and ranging system based on digital fringe projection and phase shifting technique is presented. Using the phase-shift technique, points cloud with high spatial resolution and limited accuracy can be generated. Stereo-pair images obtained from two cameras can be used to compute 3D world coordinates of a point using traditional active triangulation approach, yet the camera calibration is crucial. Neural network is a well-known approach to approximate a nonlinear system without an explicit physical model, in this work it is used to train the stereo vision application system to calculating 3D world coordinates such that the camera calibration can be bypassed. The training set for neural network consists of a variety of stereo-pair images and the corresponding 3D world coordinates. The picture elements correspondence problem is solved by using projected color-coded fringes with different orientations. Color imbalance is completely eliminated by the new color-coded method. Once the high accuracy correspondence of 2D images with 3D points is acquired, high precision 3D points cloud can be recognized by the well trained net. The obvious advantage of this approach is that high spatial resolution can be obtained by the phase-shifting technique and high accuracy 3D object point coordinates are achieved by the well trained net which is independent of the camera model works for any type of camera. Some experiments verified the performance of the method.展开更多
神经辐射场(NeRF)在二维图像到三维场景重建领域展现出优异的性能,使用二维图像作为训练数据,能够重建出场景的三维结构,并能进行高质量的新视图渲染。尽管NeRF在三维场景重建领域是十分有效的,但也存在训练速度慢、推理时间长的问题,...神经辐射场(NeRF)在二维图像到三维场景重建领域展现出优异的性能,使用二维图像作为训练数据,能够重建出场景的三维结构,并能进行高质量的新视图渲染。尽管NeRF在三维场景重建领域是十分有效的,但也存在训练速度慢、推理时间长的问题,并且样本质量与三维场景重建质量密切关联。为解决NeRF在低样本质量情况下的高质量三维重建问题,本文使用2组不同哈希编码的NeRF来学习同一个场景,评估候选视图信息增益之间的差距来引导视图采样。提出一种基于RGB特征的下一个最优视图(next best view)导航技术新框架,该框架在稀疏训练数据上具有很强的鲁棒性,能够通过RGB特征评估捕获高信息增益的下一个最优视图,并优化NeRF训练,可以用最少的额外视图来提高新视图合成质量。通过对NeRF训练流程的优化,网络收敛速度提升大约10倍,显存占用降低39.8%,大量实验验证了该模型的有效性和鲁棒性。展开更多
文摘Neuroscience (also known as neurobiology) is a science that studies the structure, function, development, pharmacology and pathology of the nervous system. In recent years, C. Cotardo has introduced coding theory into neuroscience, proposing the concept of combinatorial neural codes. And it was further studied in depth using algebraic methods by C. Curto. In this paper, we construct a class of combinatorial neural codes with special properties based on classical combinatorial structures such as orthogonal Latin rectangle, disjoint Steiner systems, groupable designs and transversal designs. These neural codes have significant weight distribution properties and large minimum distances, and are thus valuable for potential applications in information representation and neuroscience. This study provides new ideas for the construction method and property analysis of combinatorial neural codes, and enriches the study of algebraic coding theory.
基金supported by the National Natural Science Foundation of China(81974166,32271053,and 31872774).
文摘As a main structure of the limbic system,the hippocampus plays a critical role in pain perception and chronicity.The ventral hippocampal CA1(vCA1)is closely associated with negative emotions such as anxiety,stress,and fear,yet how vCA1 neurons encode nociceptive information remains unclear.Using in vivo electrophysiological recording,we characterized vCA1 pyramidal neuron subpopulations that exhibited inhibitory or excitatory responses to plantar stimuli and were implicated in encoding stimuli modalities in naïve rats.Functional heterogeneity of the vCA1 pyramidal neurons was further identified in neuropathic pain conditions:the proportion and magnitude of the inhibitory response neurons paralleled mechanical allodynia and contributed to the confounded encoding of innocuous and noxious stimuli,whereas the excitatory response neurons were still instrumental in the discrimination of stimulus properties.Increased theta power and theta-spike coupling in vCA1 correlated with nociceptive behaviors.Optogenetic inhibition of vCA1 pyramidal neurons induced mechanical allodynia in naïve rats,whereas chemogenetic reversal of the overall suppressed vCA1 activity had analgesic effects in rats with neuropathic pain.These results provide direct evidence for the representations of nociceptive information in vCA1.
文摘By mcans of stable attractors of discret Hopfield neural network (DHNN) , anew class of nonlinear error control codes is sugsested and some relativetheorems are presented. A kind of single error control codes is also given forillustrating this new approach.
文摘Presents the fuzzy neural network optimized by hybrid coded genetic algorithm of decimal encoding and binary encoding, the searching ability and stability of genetic algorithms enhanced by using binary encoding during the crossover operation and decimal encoding during the mutation operation, and the way of accepting new individuals by probability adopted, by which a new individual is accepted and its parent is discarded when its fitness is higher than that of its parent, and a new individual is accepted by probability when its fitness is lower than that of its parent. And concludes with calculations made with an example that these improvements enhance the speed of genetic algorithms to optimize the fuzzy neural network controller.
文摘A method of assigning binary indexes to codevectors in vector quantization (VQ)system, which is called pseudo-Gray coding, is presented in this paper by constructing a kind of Hopfield neural network. Pseudo-Gray coding belongs to joint source/channel coding, which could provide a redundancy-free error protection scheme for VQ of analog signals when the binary indexes of signal codevectors are used as channel symbols on a discrete memoryless channel. Since pseudo-Gray coding is of combinatorial optimization problems which are NP-complete problems,globally optimal solutions are generally impossible. Thus, a kind of Hopfield neural network is used by constructing suitable energy function to get sub-optimal solutions. This kind of Hop field neural network is easily modified to solve simplified version of pseudo-Gray coding for single bit-error channel model. Simulating experimental results show that the method introduced here could offer good performances.
基金Supported by the Eleventh Five-Year Pre-research Project of China.
文摘A new 3D surface contouring and ranging system based on digital fringe projection and phase shifting technique is presented. Using the phase-shift technique, points cloud with high spatial resolution and limited accuracy can be generated. Stereo-pair images obtained from two cameras can be used to compute 3D world coordinates of a point using traditional active triangulation approach, yet the camera calibration is crucial. Neural network is a well-known approach to approximate a nonlinear system without an explicit physical model, in this work it is used to train the stereo vision application system to calculating 3D world coordinates such that the camera calibration can be bypassed. The training set for neural network consists of a variety of stereo-pair images and the corresponding 3D world coordinates. The picture elements correspondence problem is solved by using projected color-coded fringes with different orientations. Color imbalance is completely eliminated by the new color-coded method. Once the high accuracy correspondence of 2D images with 3D points is acquired, high precision 3D points cloud can be recognized by the well trained net. The obvious advantage of this approach is that high spatial resolution can be obtained by the phase-shifting technique and high accuracy 3D object point coordinates are achieved by the well trained net which is independent of the camera model works for any type of camera. Some experiments verified the performance of the method.
文摘现有的基于卷积神经网络(convolutional neural network,CNN)的环路滤波器倾向于将多个网络应用于不同的量化参数(quantization parameter,QP),消耗训练模型中的大量资源,并增加内存负担。针对这一问题,提出一种基于CNN的QP自适应环路滤波器。首先,设计一个轻量级分类网络,按照滤波难易程度将编码树单元(coding tree unit,CTU)划分为难、中、易3类;然后,构建3个融合了特征信息增强融合模块的基于CNN的滤波网络,以满足不同QP下的3类CTU滤波需求。将所提出的环路滤波器集成到多功能视频编码(versatile video coding,VVC)标准H.266/VVC的测试软件VTM 6.0中,替换原有的去块效应滤波器(deblocking filter,DBF)、样本自适应偏移(sample adaptive offset,SAO)滤波器和自适应环路滤波器。实验结果表明,该方法平均降低了3.14%的比特率差值(Bjøntegaard delta bit rate,BD-BR),与其他基于CNN的环路滤波器相比,显著提高了压缩效率,并减少了压缩伪影。
文摘神经辐射场(NeRF)在二维图像到三维场景重建领域展现出优异的性能,使用二维图像作为训练数据,能够重建出场景的三维结构,并能进行高质量的新视图渲染。尽管NeRF在三维场景重建领域是十分有效的,但也存在训练速度慢、推理时间长的问题,并且样本质量与三维场景重建质量密切关联。为解决NeRF在低样本质量情况下的高质量三维重建问题,本文使用2组不同哈希编码的NeRF来学习同一个场景,评估候选视图信息增益之间的差距来引导视图采样。提出一种基于RGB特征的下一个最优视图(next best view)导航技术新框架,该框架在稀疏训练数据上具有很强的鲁棒性,能够通过RGB特征评估捕获高信息增益的下一个最优视图,并优化NeRF训练,可以用最少的额外视图来提高新视图合成质量。通过对NeRF训练流程的优化,网络收敛速度提升大约10倍,显存占用降低39.8%,大量实验验证了该模型的有效性和鲁棒性。
