… the information is directly transmitted without any additional coding. … the relationship between
deep learning and wireless communication … Backpropagation, kayıp fonksiyonunun model …

… Abstract In recent years,deep learning has been widely used in many fields with its … (LSTM)model
of recurrent neural networks(RNN)is used to construct the acoustic model in speech …

… not only after announcement, but also before advertising, ie they can be one step ahead by
predicting the future through … to reach the stable backpropagation. DeTienne and DeTienne [8…

… defect of online learning can be attributed to the requirement for continual true values.
Engineering problems often require models to predict many time steps into the future without the …

… reviewed the technologies of deep neural network (DNN) … 复杂度从O(No 2 Nk 2) 降低到
O(No 2lbNo)(No) 为特征图尺寸,… Backpropagation through time: What it does and how to do it [J]…

… of deep learning and enhance the interpretability of deep … Backpropagation and
levenberg-marquardt algorithm for training … and uncertainty quantification without labeled data[J]. …

… optical system based on deep neural network AI methods[34-… In situ optical backpropagation
training of diffractive optical … and diffraction models involving physical optics not only …

… Then, in context of physical layer, link layer and network layer respectively, the key
issues regarding channel modeling, waveform design, networking protocol and intelligent …

… 特性能應用於車輛聯網的最大優勢,5G 網路的時延性 (Latency of Over-the-Air)低於1 毫秒,且用戶
間的時延性(Latency of End-to… 四,以應用機器學習(Machine Learning)辨識發射機之相關 研究 …

… Although the network structure that we used here was specific to the Bovet-Pfeifer model,
we think the obtained results do not depend on the detailed architecture of the …