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[Marco Study notes] The production of Linux system bootable Linux with network function

- - For LIB in ' LDD $ | grep-o "/.*lib\ (64\) \{0,1\}/[^[:space:]]\{1,\}" ';d o the libcp $LIB - Done - } - read-p "Your Command:" CMD + until [$CMD = = ' Q ']; do - ! which $CMD >/dev/null echo "wrong command" read-p "Input again:" CMD Continue + command= ' which $CMD | grep-v "^alias" | grep-o "[^[:space:]]\{1,\}" A BINCP $COMMAND at echo "Copy $COMMAND finished." - read-p "continues:" CMD - DoneView Code5. Writing/mnt/sysroot/sbin/init files1#!/bin/Bash2 #3 Echo-E"Welcome to \033[34

Also large self-study 51cto--cisco Network device command

"1" resolves the cisco switch password forgetting reset method:1, power off + the front panel hold down the mode key, and then re-power, always press the switch front panel port 1 indicates from green to off does not light off, automatically into the switch mode;2, input? See what configuration commands are (optional), enter "Flash-init" reset initialization, enter "Load-helper" to load the Help file, and see what "Dir flash" is in the Flash file. Find profile (Password in config file profile na

"Turn" cyclic neural network (RNN, recurrent neural Networks) study notes: Basic theory

Transfer from http://blog.csdn.net/xingzhedai/article/details/53144126More information: http://blog.csdn.net/mafeiyu80/article/details/51446558http://blog.csdn.net/caimouse/article/details/70225998http://kubicode.me/2017/05/15/Deep%20Learning/Understanding-about-RNN/RNN (recurrent Neuron) is a neural network for modeling sequence data. Following the bengio of the probabilistic language model based on neural networ

CCNA Study Notes (i) Network Interconnection Foundation

three-time handshake);② using sorting techniques;③ use confirmation;④ uses flow control.34, flow control methods include buffering, window technology and congestion avoidance.35, Window Technology:The number of data segments that can be sent is called a window in order to increase the transmission efficiency of the data segment that can be transmitted during the time the sender sends the data segment to the receiving acknowledgement.The window is used to control the number of unacknowledged dat

Case study-network performance reduction caused by attacks

Case study-network performance reduction caused by attacksFault description The manager of donghuantuo Mining Network reported that many users in the region had access to the Intranet of the group company or the Internet was slow or inaccessible. The linnancang mining report said that the Headquarters network was fault

VirtualBox network/study Environment setup for RHEL

I re-visited The RHEL study material and setup the environment again, noted down the procedure.1, copied the *.VDI (RHEL6STD.VDI and RHEL6-STUDENT.VDI) file from Lenovo ThinkPad T400 to my new Lenovo ThinkPad X1, Crea Ted the new machine is importing the *.VDI, no need to install the system again.2, setup the network at Linux instructor and Linux StudentIn VirtualBox Manager, file->preferences...->

Case study of wireless network technology (III)

In the previous article, we introduced the relevant industrial art basics and wireless communication technology applications in wireless network technology applications. For details, refer to "wireless network technology application case study 1". "wireless network technology application case

Study on neural network Hopfield

Number')The above buy-in for displaying pictures and adding noise after displaying pictures, there is no need for analysis.%------------------------plot identify figure---------------------------Noise1={(Noise_one)'};% the diagram into a cell structure and transpose (horizontal picture arrangement)Tu1=sim (net,{ A,3},{},noise1);% per 12 megapixels is a pictureSubplot (2,3,3)% back to the picture and show, here to add, {3} indicates that there are three layers of neural

Zheng Jie "machine Learning algorithm principles and programming Practices" study notes (sixth. Neural network) 6.3 Self-organizing feature map neural networks (SMO)

ifSelf. Steps dm:self. Steps= 5*DM#set the minimum number of iterations forIinchxrange (self. Steps): Lrate,r= Self.ratecalc (i)#1) Calculate the learning rate and the classification radius under the current iteration countself.lratelist.append (lrate) self.rlist.append (R)#2) Randomly generate a sample index and extract a sampleK =random.randint (0,DM) mysample=normdataset[k,:]#3) Calculate the optimal node: Returns the index value of the minimum distanceMinindx =[self.disteclud

The reinforcement study guess who I am---deep q-network ^_^

*New_model[np.argmax (Old_model)] Self.model.fit (State,target,epochs=1,verbose=0)ifSelf. Esplion>Self . Esplion_min:self. Esplion*=Self . Esplion_decayclassdqnagent (Agent):defLearn (self):ifLen (self.memory) batch_size:returnMinibach=random.sample (self.memory,batch_size) forState,action,reward,next_state,doneinchMinibach:target=Rewardif notDone:target=reward+self. gamma*Np.amax (Self.model.predict (Next_State) [0]) Target_f=self.model.predict (state) target_f[0][action]=Target Self.model.fit

Wunda Deep Learning notes Course4 WEEK2 a deep convolutional network case study

1.why Look in case study This week we'll talk about some typical CNN models, and by learning these we can deepen our understanding of CNN and possibly apply them in practical applications or get inspiration from them. 2.Classic Networks The LENET-5 model was presented by Professor Yann LeCun in 1998 and is the first convolutional neural network to be successfully applied to digital recognition. In the mnis

Linux study Notes-network communication commands, system shutdown, shell application skills

Network Communication commands, system shutdown, shell application tips for Linux Study Notes 1. network communication commands www.2cto. com1. send a message to an individual. this person must write the online status user name. 2. send the message to the owner. you do not need to add the user name, as long as you log on to the linux system...

Linux 18th Day Self-study network management

Tags: time ifconfig text metrics temporary echo help stat spaceLinux 18th Day Self-study network managementTime: 20180804DirectoryIfconfigIpGUI Configuration NetworkConfiguration file Modify NIC parametersRouting Management IP, routeCommon network detection Tools ping, traceroute, SS, Netstat, Iftop, MTR, nethogsLinux Network

A study record of CNN convolutional Neural Network

weight reproduction) and time or spatial sub-sampling to obtain some degree of displacement, scale and deformation invariance.3. CNN TrainingThe training algorithm is similar to the traditional BP algorithm. It consists of 4 steps, and these 4 steps are divided into two stages:The first stage, the forward propagation phase:A) Take a sample (X,YP) from the sample set and input X into the network;b) Calculate the corresponding actual output op.At this

RCNN Study Notes (8): Fully convolutional Networks for Semantic segmentation (full convolutional network FCN)

the end, parameter learning or using the principle of the reverse propagation of CNN itself , "whole image training is effective and efficient. "3, do not limit the size of the input picture, do not require all the pictures in the picture set is the same size, just in the last upsampling by the original image is subsampling scale back , the final output will be the same size as the original dense Prediction Map. DefectsAccording to the experiment shown in the conclusion section of the paper, th

Unix study--aix 6.1 Configuring the Network installation Service

Unix study--aix 6.1 Configuring the Network installation Service The network installation reduces the maintenance burden on administrators and allows the installation of AIX systems to be deployed in batches.First, configure the network installation server1) server-side configuration# Prtconf|moresystemmodel:ibm,9131-5

Case study of docker swarm construction and cross-host network interconnection, dockerswarm

Case study of docker swarm construction and cross-host network interconnection, dockerswarm 1. Open relevant ports firewall-cmd --zone=public --add-port=2377/tcp --permanentfirewall-cmd --zone=public --add-port=7946/tcp --permanentfirewall-cmd --zone=public --add-port=7946/udp --permanentfirewall-cmd --zone=public --add-port=4789/tcp --permanentfirewall-cmd --zone=public --add-port=4789/udp --permanentfirew

Daydayup_python Self-study tutorial [13]_ Network programming

' %(CTime (), Data.decode ())). Encode (), addr)Print("Receive from %s:%s"% addr) Udpsersock.Close()udpclient.py#!/usr/bin/python#-*-Coding:utf-8-*-#udpServer. PYImportSocketFrom TimeImport CTime HOST =Socket. GetHostName () PORT =54321BUFSIZE =1024x768ADDR = (HOST, PORT) Udpsersock =Socket.Socket(Socket. Af_inet,Socket. SOCK_DGRAM) Udpsersock.Bind(ADDR) whileTrue:Print(' Waiting for message ... ') data,addr = Udpsersock.recvfrom (BUFSIZE)Print(data) Udpsersock.sendto (' [%s]%s ' %(CTime (), Da

Linux study notes virtual private network VPN experiment PPTP

Article title: Linux study notes virtual private network VPN experiment PPTP. Linux is a technology channel of the IT lab in China. Includes basic categories such as desktop applications, Linux system management, kernel research, embedded systems, and open source. The full name of VPN is "Virtual Private Network", which is translated as "Virtual Private

TensorFlow Study Note Five: mnist example-convolutional neural Network (CNN)

= Tf.nn.relu (conv2d (h_pool1, w_conv2) + b_conv2)#A second convolutional layerH_pool2 = Max_pool (h_conv2)#Second pooled layerW_FC1= Weight_variable ([7 * 7 * 64, 1024]) B_fc1= Bias_variable ([1024]) H_pool2_flat= Tf.reshape (H_pool2, [-1, 7*7*64])#reshape into VectorH_FC1 = Tf.nn.relu (Tf.matmul (H_pool2_flat, W_FC1) + b_fc1)#first fully connected layerKeep_prob= Tf.placeholder ("float") H_fc1_drop= Tf.nn.dropout (H_FC1, Keep_prob)#Dropout LayerW_FC2= Weight_variable ([1024, 10]) B_FC2= Bias_v

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