Scanning radio的問題,透過圖書和論文來找解法和答案更準確安心。 我們找到下列懶人包和總整理

Scanning radio的問題,我們搜遍了碩博士論文和台灣出版的書籍,推薦寫的 Advances in Vlsi, Communication, and Signal Processing: Select Proceedings of Vcas 2018 和的 Advances in 3D Image and Graphics Representation, Analysis, Computing and Information Technology: Algorithms and Applications, P都 可以從中找到所需的評價。

另外網站All Receivers and Scanners - Martin Lynch & Sons也說明:All Receivers and Scanners products from Ham Radio. Specialising in new & used Ham (Amateur) Radio, Commercial Two-Way Radio, ...

這兩本書分別來自 和所出版 。

國立陽明交通大學 電子研究所 林鴻志所指導 葉宇婕的 具有綠光雷射結晶多晶矽通道之T型閘薄膜電晶體射頻特性分析 (2021),提出Scanning radio關鍵因素是什麼,來自於薄膜電晶體、多晶矽、雷射結晶、T型閘極、射頻元件。

而第二篇論文嶺東科技大學 資訊科技系碩士班 張安成所指導 陳宥任的 具有混合粒子群最佳化和蝙蝠演算法之混合數位與類比波束構成 (2021),提出因為有 巨量、多輸入多輸出、波束構成、混合類比和數位、群體智慧、粒子群最佳化、蝙蝠演算法、混合方法的重點而找出了 Scanning radio的解答。

最後網站How Scanning Works | Tait Radio ... - The Tait Radio Academy則補充:A better way of doing this is a process called scanning. This enables the radio to automatically check each channel in turn, one after the other to see if ...

接下來讓我們看這些論文和書籍都說些什麼吧:

除了Scanning radio,大家也想知道這些:

Advances in Vlsi, Communication, and Signal Processing: Select Proceedings of Vcas 2018

為了解決Scanning radio的問題,作者 這樣論述:

BER Performance Evaluation of Different Modulation Techniques for Underwater FSO Communication System.- Reliable Location-Aware Routing Protocol for Urban Vehicular Scenario.- Temperature Dependent Analog, RF and Linearity Analysis of Junctionless Quadruple Gate MOSFETs for Analog Applications.- Per

formance of Double Gate Tunnel FET Devices with Source Pocket.- Image compression Using hybrid approach and adaptive scanning for color images.- Sparse Matrix Completion for Effective Recommendation System.- Enhanced XOR-based Progressive Visual Secret Sharing Using Multiple Decryptions.- EEG Seizur

e Detection from Compressive Measurements.- Noise cancellation using Adaptive Filter.- A Novel Approach for Compensation of Light Variation Effects with KELM Classification for Efficient Face Recognition.- A Hybridization of Fuzzy Logic and Deterministic Learning Machine for Face Recognition. Dr.

Debashis Dutta obtained his Masters from the Electrical Engineering department of Indian Institute of Technology, Delhi and his PhD in Electronics and Electrical Communication Engineering from Indian Institute of Technology, Kharagpur. He worked as Scientist G and Group Coordinator (R&D in Electroni

cs Group) in the Ministry of Electronics and Information Technology (MeitY), Government of India. Dr. Dutta has also worked as Programme Director for Special Manpower Development Program (SMDP) in VLSI Design. He was the Director in the board of NICSI, a society under National Informatics Centre and

Governing Council member in several R&D institutions. Currently, he works as a consultant for various academic institutions and electronics manufacturing industries. His research interests include low-power analog circuit design, biomedical electronics and neural networks.Dr. Haranath Kar received

his Bachelors from Bengal Engineering College, Shibpur (now IIEST) in 1989, his Masters from Banaras Hindu University, Varanasi in 1992 and his PhD from the University of Allahabad in 2000. After spending a brief period at the Defence Research and Development Organization as Scientist B, he joined M

otilal Nehru National Institute of Technology (MNNIT), Allahabad, India, as a Lecturer in 1991, where he became an Assistant Professor in 2001, Associate Professor in2006 and Professor in 2007. He spent two years at the Atilim University, Turkey (2002-2004) as an Assistant Professor. He was Head of

Electronics and Communication Engineering Department at MNNIT during 2013-2015. His current research interests include digital signal processing, nonlinear dynamical systems, delayed systems, robust stability, guaranteed cost control, and multidimensional systems. He is a recipient of the 2002-2003

IEE Heaviside Premium Award. He was conferred with the D.N. Agrawal Award of excellence and the Bharat Vikas Award in 2005 and 2017, respectively. He is also a member of editorial board of the Mathematical Problems in Engineering.Dr. Chiranjeev Kumar received his Bachelors in Telecommunication Engin

eering from Banglore University, his Masters in Computer Science, and his PhD from MNNIT Allahabad. Currently, he is a professor in the Department of Computer Science & Engineering, Indian Institute of Technology (IIT-ISM), Dhanbad, India. His research interests include wireless networks, software e

ngineering, mobility management, and cognitive radio networks. He has published more than 100 articles in international journals and conferences proceedings. Dr. Kumar has also contributed several books and book chapters on wireless communication and networking, and he has worked as an ad hoc review

er of many international journals.Dr. Vijaya Bhadauria received her Bachelors (Electronics) and Masters (Control & Instrumentation), and her PhD in Electronics Engineering from MNNIT Allahabad. At present, she is Professor and Head in the Department of Electronics & Communication Engineering, MNNIT

Allahabad. Her major research interests include VLSI circuits and system, digital integrated circuit design, advanced analog integrated circuit design, VLSI technology and Semiconductor Device and Modeling. She has published many papers in international journals and proceedings, and has also acted a

s an ad hoc reviewer of many international journals.

具有綠光雷射結晶多晶矽通道之T型閘薄膜電晶體射頻特性分析

為了解決Scanning radio的問題,作者葉宇婕 這樣論述:

本論文中,我們研究具有T型閘極、空氣邊襯及矽化閘/源/汲極多晶矽薄膜電晶體的射頻特性。為了提升多晶矽薄膜的晶粒尺寸,我們使用綠光奈秒雷射來製備厚度為50 nm與100 nm的多晶矽薄膜。結果顯示厚度為100 nm的薄膜能得到等效尺寸大於1 μm的晶粒大小,遠優於50 nm厚的多晶矽薄膜。我們於元件製作時採用了新穎的T型閘極技術,不僅降低元件的閘極電阻,也使電晶體具有比微影技術解析極限更小的閘極線寬,使轉導得以大幅提升。我們也分別利用高溫的快速熱退火及低溫的微波退火來活化源汲極雜質。在通道厚度為100 nm並以快速熱退火進行源汲極活化的多晶矽薄膜電晶體中,對最小通道長度達124 nm之元件,截

止頻率可達59.7 GHz,最大震盪頻率亦可達34 GHz。具有相同通道厚度並以微波退火來活化雜質的電晶體中,當通道長度微縮至102 nm,元件的截止頻率更高達63.6 GHz,最大震盪頻率亦可達29.7 GHz。相較過往文獻報導的多晶矽薄膜元件,我們以微波活化源汲極的薄膜電晶體達到了最高的截止頻率。

Advances in 3D Image and Graphics Representation, Analysis, Computing and Information Technology: Algorithms and Applications, P

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為了解決Scanning radio的問題,作者 這樣論述:

1. 3D-Digital Image Correlation Technique for Strain Measurement in Fiber reinforced polymer Strip Externally Bonded to Concrete Specimens.- 2. Establishment of Quality Detection and 3D Evaluation Model of Wool FabricBased on Machine Vision.- 3. The Research and Design of Wage Supervision Service Pl

atform for Migrant Workers Based on Big Data and Iris Recognition Technology.- 4. Research on Block Segmentation and Assembly Technology of 3D Printing Structure.- 5. A Study on 3D Reconstruction Method for Common View Field in Hybrid Vision System.- 6. Three-Dimensional Characteristics Observation

of Ocean Waves in Coastal Areas by Microwave Doppler Radar.- 7. Three-dimensional Reconstruction Based on Left and Right Objects.- 8. Research on 3D Scene Dynamic Scanning Modeling Technology of Substation Based on Depth Vision Prof. Dr. Roumen Kountchev, D.Sc., works at the Faculty of Telecommuni

cations, Department of Radio Communications and Video Technologies--Technical University of Sofia, Bulgaria. He has published 341 papers in journals and conference proceedings, 15 books and 46 book chapters, and holds 20 patents. He is a member of the Euro Mediterranean Academy of Arts and Sciences;

President of the Bulgarian Association for Pattern Recognition (member of IAPR); and editorial board member of the IJBST Journal Group, International Journal of Reasoning-based Intelligent Systems, and the international journal Broad Research in Artificial Intelligence and Neuroscience. Prof. Dr. S

rikanta Patnaik works at the Department of Computer Science and Engineering, Faculty of Engineering and Technology, SOA University, Bhubaneswar, India. He has published over 100 papers in international journals and conference proceedings, 2 textbooks and 32 edited volumes. He is the editor-in-chief

of the International Journal of Information and Communication Technology, the International Journal of Computational Vision and Robotics (Inderscience Publishing House) and the book series Modeling and Optimization in Science and Technology (Springer), Advances in Computer and Electrical Engineering

, and Advances in Medical Technologies and Clinical Practices (IGI-Global). Prof. Dr. Junsheng Shi is the Dean of the School of Physics and Electronic Information, Yunnan Normal University. He is a member of China Illuminating Engineering Society Image Technology Specialized Committee, the China Opt

ical Technology Optical Society Professional Committee, and the Chinese Society of Image and Graphics Technical Committee on stereoscopic imaging. He also contributes to the journals Optical Engineering and the Journal of Display Technology. In 2004 and 2008, he received awards for scientific and te

chnological progress and natural science in Yunnan Province. In the last five years, he has completed two major projects and published over 50 papers.Prof. Dr. Margarita Favorskaya is the Head of the Department of Informatics and Computer Techniques at Reshetnev Siberian State University of Science

and Technology, RF. She is an IPC member and has chaired invited sessions at over 30 international conferences. She is a reviewer for various journals: Neurocomputing, Knowledge Engineering and Soft Data Paradigms, Pattern Recognition Letters, and Engineering Applications of Artificial Intelligence,

and an associate editor of Intelligent Decision Technologies Journal, International Journal of Knowledge-Based Intelligent Engineering Systems and the International Journal of Reasoning-based Intelligent Systems. She is also a reviewer and book editor for Springer.

具有混合粒子群最佳化和蝙蝠演算法之混合數位與類比波束構成

為了解決Scanning radio的問題,作者陳宥任 這樣論述:

混合數位和類比(hybrid digital and analog, HDA)波束構成作為一種有效且有前途的技術,在巨量多輸入多輸出系統已成為近年來受歡迎的研究議題。相較於全數位的波束構成,部分連接的HAD波束構成是可以明顯降低硬體成本、複雜性和功率消耗。對於傳統HAD波束構成器設計,類比權重部分係採用精細格柵的頻譜線性搜尋之類比相位校正(analog phase correction by spectrum searching, APCSS)程序來最佳化類比波束構成器矩陣,其次引入最小無失真響應(minimum variance distortionless response, M

VDR)或基於特徵空間波束構成於數位權重向量的最佳化。 本論文處理基於群體智慧最佳化的混合數位和類比(HDA)波束構成器,用以減輕由於透過減少所需的射頻鏈路數目來降低硬體複雜性和成本所產生的干擾。這些所提方案係透過混合數位和類比(HDA)來最大化系統輸出訊號與干擾加雜訊比,首先簡化適應度函數來解決最佳化問題,由於適應函數的計算複雜度和估測精準度與搜尋格柵尺寸和搜尋範圍大小有密切關係,故本論文引入粒子群最佳化(particle swarm optimization, PSO)和蝙蝠演算法(bat algorithm, BA)對類比和數位部份的權重進行全域最佳解的搜尋,不僅可避免格柵尺寸之不

確定先驗決定的困境,亦可降低傳統窮舉式空間搜尋所需之計算複雜度;本論文還利用PSO和BA的優勢提出了兩種混合演算法,主要想法是整合 PSO 的開採(exploitation)能力和 BA 的探勘(exploration)能力。最後,藉由電腦模擬結果驗證這些所提方法的有效性。