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readme

INTRODUCTION lwIP is a small independent implementation of the TCP/IP protocol suite that has been developed by Adam Dunkels at the Computer and Networks Architectures (CNA) lab at the Swedish Instit
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readme

An experment demonstrating the performance of 12 different propagation and radio model combinations with AODV and DSR from, "Effects of Wireless Physical Layer Modeling in Mobile Ad Hoc Networks",
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readme

INTRODUCTION lwIP is a small independent implementation of the TCP/IP protocol suite that has been developed by Adam Dunkels at the Computer and Networks Architectures (CNA) lab at the Swedish Instit
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www.eeworm.com/read/253785/4392162

m ttsendmsg.m

% TTSENDMSG Send a message over a network. % This function is used both for wired and wireless networks. % % Usage: ttSendMsg(receiver, data, length) % ttSendMsg(receiver, data,
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readme

An experment demonstrating the performance of 12 different propagation and radio model combinations with AODV and DSR from, "Effects of Wireless Physical Layer Modeling in Mobile Ad Hoc Networks",
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www.eeworm.com/read/155551/5620840

readme

INTRODUCTION lwIP is a small independent implementation of the TCP/IP protocol suite that has been developed by Adam Dunkels at the Computer and Networks Architectures (CNA) lab at the Swedish Instit
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www.eeworm.com/read/154801/5634412

readme

INTRODUCTION lwIP is a small independent implementation of the TCP/IP protocol suite that has been developed by Adam Dunkels at the Computer and Networks Architectures (CNA) lab at the Swedish Instit
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www.eeworm.com/read/268726/11124542

txt readme.txt

McAfee(R) VirusScan(R) Enterprise 8.0i 版 Patch 1 发行说明 Copyright (C) 2004 Networks Associates Technology, Inc.
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www.eeworm.com/read/200737/15426319

c router_app.c

/* V0.1 Initial Release 10/July/2006 RBR */ /* This is intended to be a router application that recovers from dropped networks. It starts by joining a network and then runnning the
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m svctutor.m

function tutor = svctutor(arg) % SVCTUTOR % % Constructor for a class of tutor objects used to train support vector % classification networks. Note this is an abstract base class, you cannot %
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