题目:Acoustic Echo Cancellation Using Deep Complex Neural Network with Nonlinear Magnitude Compression and Phase Information 作者:Renhua Peng ,Linjuan Cheng , Chengshi Zheng, Xiaodong Li bookti…
PyTorch is a flexible deep learning framework that can be used to create complex neural networks for tasks such as super-resolution, denoising, and compression. PSRN and SSIM are two important metrics that can be used to quantitatively evaluate the performance of these methods during training and ...
ComplexNN: Complex Neural Network Modules What is ComplexNN? ComplexNN provides the plural form of standard modules under the PyTorch framework without any extra trainable parameters. The parameters and calling methods of the modules in this framework are consistent with those of the PyTorch framework...
0 Revision: Fully Connected Neural Network 之前的网络里面用的都是线性层,如果一个网络全都由线性层串行连接起来,就叫做全连接网络。在线性层里面输入和每一个输出值之间都存在权重,即每一个输入节点都要参与到下一层输出节点的计算上,这样的线性层也叫全连接层(Fully Connected)。 1 Convolutional Neural Network...
Over time since then, with more deep and complex neural networks, the classification error kept reducing and has beaten human-level performance. 在第一章节中,主要通过一个简单网络结构,让大家了解一个神经网络的基本构成(前向网络,反向传播,学习率等基础模块)。
center=False, return_complex=True)#(*, F,T)magnitude = torch.abs(S)#振幅phase = torch.exp(1j * torch.angle(S))#相位returnmagnitude, phasedef__getitem__(self, item):"""__getitem__是类的专有方法,使类可以像list一样按照索引来获取元素 ...
while theofficial examplesinclude—among other things—a deep convolutional generative adversarial network (DCGAN) and models for ImageNet andneural machine translation. Richie Ng from National University of Singapore keeps anup-to-date listof other PyTorch implementations, examples, and tutorials. The Py...
I think this technique is the most complex technique in this repository in terms of understanding what the code does. It is mainly because of complex regularization. If you truly want to understand how this is implemented I suggest you read the second and third page of the paper [5], speci...
Lifelong learning is a complex topic in machine learning, whether in combination with reinforce- ment learning or other learning methods. There are different approaches for this and one of them are hypernetworks. Hypernetworks have the advantage of having a very large ability to preserve past mem...
arises in various domains, such as image retrieval, face recognition, and object tracking. Traditional methods for image comparison often rely on handcrafted features and similarity metrics. However, these methods are limited by their inability to capture complex patterns and variations in the images....