公开(公告)号：US20160123943A1

公开(公告)日：2016-05-05

申请号：US14895915

申请日：2013-06-05

申请人： INSTITUTE OF MICROELECTRONICS, CHINESE ACADEMY OF SCIENCES

发明人： Dongmei LI ,  Hao ZHANG ,  Shengfa LIANG ,  Qing LUO ,  Xiaojing LI ,  Changqing XIE ,  Ming LIU

IPC分类号： G01N33/00

CPC分类号： G01N33/0034 ,  G06N3/084

摘要： A gas recognition method based on a compressive sensing theory. The method comprises: collecting compressed data in an under-sampling manner; performing a reconstruction on the collected compressed data to obtain reconstructed data; training a back-propagation neural network by using the reconstructed data and storing the trained back-propagation neural network; inputting data under test into the trained back-propagation neural network, such that the trained back-propagation neural network performs a recognition on the data under test to realize qualitative recognition of gas. The method solves the problem in transmission and storage of large amount of data and the problem of imprecise recognition in current gas detection, and achieves the object that a precise qualitative recognition is achieved by using a reduced amount of data.

摘要翻译： 一种基于压缩感知理论的气体识别方法。 该方法包括：以低采样方式收集压缩数据; 对所收集的压缩数据进行重构以获得重构数据; 通过使用重构数据训练反向传播神经网络，并存储经过训练的反向传播神经网络; 将被测数据输入到经过训练的反向传播神经网络中，使得经过训练的反向传播神经网络对被测数据进行识别，以实现气体的定性识别。 该方法解决了大量数据的传输和存储问题，以及当前气体检测中不精确识别的问题，达到了通过减少数据量实现精确定性识别的对象。

公开(公告)号：US20160079969A1

公开(公告)日：2016-03-17

申请号：US14888335

申请日：2013-07-15

申请人： INSTITUTE OF MICROELECTRONICS, CHINESE ACADEMY OF SCIENCES

发明人： Dongmei LI ,  Qing LUO ,  Shengfa LIANG ,  Hongzhang YANG ,  Xiaojing LI ,  Hao ZHANG ,  Changqing XIE ,  Ming LIU

IPC分类号： H03K4/08

CPC分类号： H03K4/08 ,  A61B5/00 ,  H03K3/84 ,  H03K4/50

摘要： A sampler adapted to a one-dimension slow-varying signal, including: a signal preprocessing unit configured to preprocess an input signal; a slope-controllable sawtooth wave signal generating unit configured to generate a slope-controllable sawtooth wave signal and perform zero-resetting; a signal comparing unit configured to compare the preprocessed input signal from the signal preprocessing unit with the sawtooth wave signal and to output a pulse signal to the generating unit and a signal outputting unit when the preprocessed input signal is equal to the sawtooth wave signal; a counting unit configured to count a number of clock signals while the sawtooth wave signal generating unit is generating the sawtooth wave signal and to transmit the counted number to the signal outputting unit; the signal outputting unit configured to, upon receipt of the pulse signal output from the signal comparing unit, output the number counted by the counting unit at the moment.

摘要翻译： 一种适于一维慢变信号的采样器，包括：信号预处理单元，被配置为预处理输入信号; 坡度可控锯齿波信号产生单元，其被配置为产生斜率可控锯齿波信号并执行零重置; 信号比较单元，被配置为将来自信号预处理单元的预处理输入信号与锯齿波信号进行比较，并且当预处理输入信号等于锯齿波信号时，向生成单元输出脉冲信号和信号输出单元; 计数单元，被配置为在锯齿波信号生成单元产生锯齿波信号的同时对多个时钟信号进行计数，并将计数的数量发送到信号输出单元; 所述信号输出单元被配置为在接收到从所述信号比较单元输出的脉冲信号时，输出由所述计数单元计数的数量。

公开(公告)号：US20240232592A1

公开(公告)日：2024-07-11

申请号：US18263606

申请日：2022-03-03

申请人： INSTITUTE OF MICROELECTRONICS, CHINESE ACADEMY OF SCIENCES

发明人： Xuefeng ZHAO ,  Guozhong XING ,  Di WANG ,  Ziwei WANG ,  Long LIU ,  Huai LIN ,  Hao ZHANG

IPC分类号： G06N3/063

CPC分类号： G06N3/063

摘要： Provided are a reconfigurable neuron device based on ion gate regulation and a method of preparing the same. The device includes: a synthetic antiferromagnetic layer, a metal oxide layer, an ionic liquid layer and a top electrode layer which are sequentially stacked from bottom to top. A left boundary antiferromagnetic layer and a right boundary antiferromagnetic layer having opposite magnetization directions are provided on two opposite edges of a bottom end of the synthetic antiferromagnetic layer, and a magnetic tunnel junction configured to output a spike signal is further provided in a middle portion of the bottom end of the synthetic antiferromagnetic layer. The metal oxide layer, the ionic liquid layer and the top electrode layer constitute an ion gate, the ionic liquid layer includes a positive ion and a negative ion.

公开(公告)号：US20150326246A1

公开(公告)日：2015-11-12

申请号：US14805868

申请日：2015-07-22

申请人： Institute of Microelectronics, Chinese Academy of Sciences

发明人： Dongmei LI ,  Xiaojing LI ,  Shengfa LIANG ,  Hao ZHANG ,  Qing LUO ,  Changqing XIE ,  Ming LIU

IPC分类号： H03M7/30

CPC分类号： H03M7/3062 ,  H03M7/30 ,  H04L27/2642

摘要： A method for collecting a signal with a frequency lower than a Nyquist frequency includes, by a data transmitting end, selecting a suitable transformation base matrix for an input signal, deriving a sparse representation of the signal using the transformation base matrix to determine a sparsity of the signal, calculating a number M of compressive sampling operations according to the sparsity, sampling the signal with fNYQ/M using M channels, and integrating sampling values of each channel to obtain M measurement values. A reconstruction end reconstructs an original signal by solving optimization problems. Based on theory, compressive sampling can be performed on a sparse signal or a signal represented in a sparse manner with a frequency much lower than the Nyquist frequency, overcoming restrictions of the typical Nyquist sampling theorem. The method can be implemented simply and decrease pressure on data collection, storage, transmission and processing.

摘要翻译： 收集频率低于奈奎斯特频率的信号的方法包括：通过数据发送端，为输入信号选择合适的变换基矩阵，使用变换基矩阵导出信号的稀疏表示，以确定稀疏度 信号，根据稀疏度计算M个压缩采样操作，使用M个通道对fNYQ / M采样信号，并对每个通道的采样值进行积分以获得M个测量值。 重建结束通过解决优化问题重建原始信号。 基于理论，可以对稀疏信号或以稀疏方式表示的信号执行压缩采样，频率远低于奈奎斯特频率，克服典型奈奎斯特采样定理的限制。 该方法可以简单实现，减少数据收集，存储，传输和处理的压力。