msp430The LDC1312 and LDC1314 are 2- and 4-channel, 1? Easy-to-use – minimal configuration required 12-bit inductance to digital converters (LDCs) for ? Measure up to 4 sensors with one IC inductive sensing solutions. With multiple channels ? Multiple channels support environmental and and support for remote sensing, the LDC1312 and aging compensation LDC1314 enable the performance and reliability benefits of inductive sensing to be realized at minimal? Multi-channel remote sensing provides lowest cost and power. The products are easy to use, onlysystem cost requiring that the sensor frequency be within 1 kHz ? Pin-compatible medium and high-resolution and 10 MHz to begin sensing. The wide 1 kHz to 10 options MHz sensor frequency range also enables use of very small PCB coils, further reducing sensing– LDC1312/4: 2/4-ch 12-bit LDC solution cost and size.– LDC1612/4: 2/4-ch 28
上傳時間： 2016-07-22
上傳用戶：tongmoonsky
The CommScope InstaPATCH? 360 and ReadyPATCH? solutions utilize a standards-compliant multi-fiber connector to provide high density termination capability. The connector is called an MPO (Multi-fiber Push On) connector by the standards. In many cases, multi-fiber connector products are referred to as MTP connectors. This document is intended to clarify the difference between the two terms – MPO and MTP.
上傳時間： 2017-04-12
上傳用戶：asdfghjkl1234567890
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標(biāo)簽： 源代碼
上傳時間： 2017-11-17
上傳用戶：wendingchang
Reconstruction- and example-based super-resolution (SR) methods are promising for restoring a high-resolution (HR) image from low-resolution (LR) image(s). Under large magnification, reconstruction-based methods usually fail to hallucinate visual details while example-based methods sometimes introduce unexpected details. Given a generic LR image, to reconstruct a photo-realistic SR image and to suppress artifacts in the reconstructed SR image, we introduce a multi-scale dictionary to a novel SR method that simultaneously integrates local and non-local priors. The local prior suppresses artifacts by using steering kernel regression to predict the target pixel from a small local area. The non-local prior enriches visual details by taking a weighted average of a large neighborhood as an estimate of the target pixel. Essentially, these two priors are complementary to each other. Experimental results demonstrate that the proposed method can produce high quality SR recovery both quantitatively and perceptually.
標(biāo)簽： Super-resolution Multi-scale Dictionary Single Image for
上傳時間： 2019-03-28
上傳用戶：fullout
C#遠(yuǎn)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(biāo)簽： QuasarRAT
上傳時間： 2019-04-21
上傳用戶：netangels
在微電網(wǎng)調(diào)度過程中綜合考慮經(jīng)濟(jì)、環(huán)境、蓄電池的 循環(huán)電量，建立多目標(biāo)優(yōu)化數(shù)學(xué)模型。針對傳統(tǒng)多目標(biāo)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(biāo)粒子群算法 (multi-objective particle swarm optimization algorithm based on fuzzy clustering，F(xiàn)CMOPSO)，在迭代過程中引入模糊聚 類分析來尋找每代的集群最優(yōu)解。與 MOPSO 相比， FCMOPSO 增強了算法的穩(wěn)定性與全局搜索能力，同時使優(yōu) 化結(jié)果中 Pareto 前沿分布更均勻。在求得 Pareto 最優(yōu)解集 后，再根據(jù)各目標(biāo)的重要程度，用模糊模型識別從最優(yōu)解集 中找出不同情況下的最優(yōu)方案。最后以一歐洲典型微電網(wǎng)為 例，驗證算法的有效性和可行性。
標(biāo)簽： 模糊 模型識別 微電網(wǎng) 多目標(biāo)優(yōu)化 聚類分析
上傳時間： 2019-11-11
上傳用戶：Dr.趙勁帥
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(biāo)簽： Programmable Networks Active and
上傳時間： 2020-05-26
上傳用戶：shancjb
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(biāo)簽： Broadband Wireless Networks
上傳時間： 2020-05-26
上傳用戶：shancjb
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(biāo)簽： Communication Systems Coding MIMO for
上傳時間： 2020-05-26
上傳用戶：shancjb
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(biāo)簽： Radio Cognitive Software Defined
上傳時間： 2020-05-26
上傳用戶：shancjb
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