搜索资源列表
matlabjuanji
- 已知两个信号序列： 用conv函数求两个序列的卷积和，并绘制三个序列的波形。(Two signal sequences are known: The convolution sum of two sequences is obtained by using the conv function, and the waveform of the three sequences is drawn.)
Sobel-Gxconvolution
- Sobel-Gx卷积结果，matlab代码(Sobel-Gx Convolution Results)
convolution_reconstruction_coin
- 该程序是用MATLAB语言，用卷积法实现实现硬币的重建过程(Three dimensional reconstruction of convolution method)
FeatureExtractionUsingAlexNetExample
- 本示例展示了怎样从一个预处理的卷积神经网络中提取特征，并用这些特征去训练一个图像分类器。(This example shows how to extract learned features from a pretrained convolutional neural network, and use those features to train an image classifier. Feature extraction is the easiest and fastest way use
MatrixConv
- 由公式写出的矩阵卷积函数，可以实现符号矩阵的卷积操作，已验证，可直接调用(The matrix convolution function written by the formula can realize the convolution operation of the symbol matrix, which has been verified and can be invoked directly.)
caffe
- 卷积神经网络的一种开源代码，可以对图像数据库自动提取特征(An open source code of the convolution neural network that automatically extracts features of an image database. (one open source code of CNN which can extract features other image dataset.))
time-domain convolution
- 主要通过labview对仿真·信号进行分析，进行时域卷积分析(The simulation signal is analyzed by LabVIEW, and the time domain convolution analysis is carried out.)
image
- cifar 卷积神经网络 通过cnn识别图片，对神经网络进行训练，在识别cifar库(convolutional neural network)
FFTJUANJI
- 快速傅里叶变换卷积，使用c++语言实现傅里叶转换程序，希望能开通下载功能，(Fast Fourier transform convolution)
01-第四课第一周编程作业
- 吴恩达人工智能课程，第四课 卷积神经网络第一周的课后练习题以及答案(The Andrew Ng artificial intelligence course, the fourth lesson of the convolution neural network after class exercises and the answer)
02-第四课第二周编程作业
- 吴恩达人工智能课程，第四课 卷积神经网络第二周的课后练习题以及答案(The Wu Enda artificial intelligence course, the fourth lesson of the convolution neural network after class exercises and the answer)
03-第四课第三周编程作业
- 吴恩达人工智能课程，第四课 卷积神经网络第三周的课后练习题以及答案(The Wu Enda artificial intelligence course, the fourth lesson of the convolution neural network after class exercises and the answer)
04-第四课第四周编程作业
- 吴恩达人工智能课程，第四课 卷积神经网络第四周的课后练习题以及答案(The Wu Enda artificial intelligence course, the fourth lesson of the convolution neural network after class exercises and the answer)
卷积码程序verilog
- 用Verilog语言在FPGA下实现卷积程序。(Convolution code utilite by verilog)
testandtrain
- 利用三层卷积神经网络识别信号星座图，准确识别8psk，16psk，32psk，64qpsk四种调制方式，在低信噪比的情况下已然有良好的识别率。(The three layer convolution neural network is used to identify signal constellation, and accurately identify four modulation modes of 8PSK, 16PSK, 32psk and 64qpsk. It has a good
deconvolution
- 时域解卷积的有关算法，med,mckd meda ,omeda,momeda等(The relevant algorithms for time domain deconvolution, Med, MCKD MEDA, omeda, momeda and so on)
cnn
- 卷积神经网络的M语言实现，包含众多子程序(Convolutional Neural Networ)
cnn
- 基于python tensorflow框架构建的卷积神经网络用来识别图像，附带训练数据集的制作代码。(The convolution neural network based on the python tensorflow framework is used to identify images with the production code of the training data set.)
卷积算法与数字滤波器
- matlab代码：卷积算法，数字滤波器，矩形窗，凯泽窗(Matlab code: convolution algorithm, digital filter)
multi-layer-convnet-master
- 深度学习中的卷积神经网络程c/c++代码简单实现(deep learning convnet network)