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multi-function

  • read_segy_file_legacy

    read_segy_file_legacy Function reads a SEG-Y file and outputs a seismic structure Last updated: April 6, 2007: fix bug in reading of user-specified header

    標簽: read_segy_file_legacy

    上傳時間: 2019-04-04

    上傳用戶:wc12

  • =read_segy_file

    Function reads a SEG-Y file and outputs a seismic structure; the function

    標簽: read_segy_file

    上傳時間: 2019-04-04

    上傳用戶:wc12

  • QuasarRAT-1.3.0.0

    C#遠控源代碼 * TCP network stream (IPv4 & IPv6 support) * Fast network serialization (NetSerializer) * Compressed (QuickLZ) & Encrypted (AES-128) communication * Multi-Threaded * UPnP Support * No-Ip.com Support * Visit Website (hidden & visible) * Show Messagebox * Task Manager * File Manager * Startup Manager * Remote Desktop * Remote Webcam * Remote Shell * Download & Execute * Upload & Execute * System Information * Computer Commands (Restart, Shutdown, Standby) * Keylogger (Unicode Support) * Reverse Proxy (SOCKS5) * Password Recovery (Common Browsers and FTP Clients) * Registry Editor

    標簽: QuasarRAT

    上傳時間: 2019-04-21

    上傳用戶:netangels

  • 基于模糊聚類分析與模型識別的微電網多目標優化方法

    在微電網調度過程中綜合考慮經濟、環境、蓄電池的 循環電量,建立多目標優化數學模型。針對傳統多目標粒子 群算法(multi-objective particle swarm optimization,MOPSO) 的不足,提出引入模糊聚類分析的多目標粒子群算法 (multi-objective particle swarm optimization algorithm based on fuzzy clustering,FCMOPSO),在迭代過程中引入模糊聚 類分析來尋找每代的集群最優解。與 MOPSO 相比, FCMOPSO 增強了算法的穩定性與全局搜索能力,同時使優 化結果中 Pareto 前沿分布更均勻。在求得 Pareto 最優解集 后,再根據各目標的重要程度,用模糊模型識別從最優解集 中找出不同情況下的最優方案。最后以一歐洲典型微電網為 例,驗證算法的有效性和可行性。

    標簽: 模糊 模型識別 微電網 多目標優化 聚類分析

    上傳時間: 2019-11-11

    上傳用戶:Dr.趙勁帥

  • 多元散射校正MSC

    function [R,k,b] = msc(A) % 多元散射校正 % 輸入待處理矩陣,通過多元散射校正,求得校正后的矩陣 %% 獲得矩陣行列數 [m,n] = size(A); %% 求平均光譜 M = mean(A,2); %% 利用最小二乘法求每一列的斜率k和截距b for i = 1:n a = polyfit(M,A(:,i),1); if i == 1 k = a(1); b = a(2); else k = [k,a(1)]; b = [b,a(2)]; end end %% 求得結果 for i = 1:n Ai = (A(:,i)-b(i))/k(i); if i == 1 R = Ai; else R = [R,Ai]; end end

    標簽: MSC 多元 散射 校正

    上傳時間: 2020-03-12

    上傳用戶:15275387185

  • Active+and+Programmable+Networks

    New applications such as video conferencing, video on demand, multi- media transcoders, Voice-over-IP (VoIP), intrusion detection, distributed collaboration, and intranet security require advanced functionality from networks beyond simple forwarding congestion control techniques. 

    標簽: Programmable Networks Active and

    上傳時間: 2020-05-26

    上傳用戶:shancjb

  • Broadband Wireless Networks

    Emerging technologies such as WiFi and WiMAX are profoundly changing the landscape of wireless broadband.  As  we evolve into future generation wireless networks, a primary challenge is the support of high data rate, integrated multi- media type traffic over a unified platform. Due to its inherent advantages in high-speed communication, orthogonal frequency division multiplexing (OFDM) has become the modem  of  choice for a number of high profile wireless systems (e.g., DVB-T, WiFi, WiMAX, Ultra-wideband).

    標簽: Broadband Wireless Networks

    上傳時間: 2020-05-26

    上傳用戶:shancjb

  • Coding+for+MIMO+Communication+Systems

    Employing multiple transmit and receive antennas, namely using multi-input multi-output (MIMO) systems, has proven to be a major breakthrough in providing reliable wireless communication links. Since their invention in the mid-1990s, transmit diversity, achieved through space-time coding, and spatial multiplexing schemes have been the focus of much research in the area of wireless communications. 

    標簽: Communication Systems Coding MIMO for

    上傳時間: 2020-05-26

    上傳用戶:shancjb

  • Cognitive+Radio,+Software+Defined+Radio

    Today’s wireless services have come a long way since the roll out of the conventional voice-centric cellular systems. The demand for wireless access in voice and high rate data multi-media applications has been increasing. New generation wireless communication systems are aimed at accommodating this demand through better resource management and improved transmission technologies.

    標簽: Radio Cognitive Software Defined

    上傳時間: 2020-05-26

    上傳用戶:shancjb

  • Coordinated+Multi-Point

    Mobile communication has gained significant importance in today’s society. As of 2010, the number of mobile phone subscribers has surpassed 5 billion [ABI10], and the global annual mobile revenue is soon expected to top $1 trillion [Inf10]. While these numbers appear promising for mobile operators at first sight, the major game-changer that has come up recently is the fact that the market is more and more driven by the demand for mobile data traffic [Cis10].

    標簽: Coordinated Multi-Point

    上傳時間: 2020-05-27

    上傳用戶:shancjb

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