2012 IEEE National Aerospace and Electronics Conference (NAECON)最新文献_第3页

A new approach to on-chip probing in the MM-wave to THz range 毫米波到太赫兹波段的片上探测新方法

2012 IEEE National Aerospace and Electronics Conference (NAECON) Pub Date : 2012-07-25 DOI: 10.1109/NAECON.2012.6531021

M. J. H. Larsen, E. Brown

引用次数: 2

Increased output power 300 GHz oscillator based on linear superposition 基于线性叠加增加输出功率的300 GHz振荡器

2012 IEEE National Aerospace and Electronics Conference (NAECON) Pub Date : 2012-07-25 DOI: 10.1109/NAECON.2012.6531022

S. Tenneti, N. Nahar, J. Volakis

引用次数: 0

An ultra-small on-chip sensor for temperature and thermal gradient measurements 用于温度和热梯度测量的超小型片上传感器

2012 IEEE National Aerospace and Electronics Conference (NAECON) Pub Date : 2012-07-25 DOI: 10.1109/NAECON.2012.6531047

Yen-Ting Wang, Chen Zhao, Degang Chen, Shu-Chuan Huang, R. Geiger

引用次数: 3

Dual-band, Wide-incident-angle absorber for far-IR and THz frequencies 双波段，宽入射角吸收器远红外和太赫兹频率

2012 IEEE National Aerospace and Electronics Conference (NAECON) Pub Date : 2012-07-25 DOI: 10.1109/NAECON.2012.6531019

Woon-Gi Yeo, N. Nahar, K. Sertel

引用次数: 0

Localization of RF emitters using compressed sensing with multiple cooperative sensors 基于多传感器协同压缩感知的射频发射器定位

2012 IEEE National Aerospace and Electronics Conference (NAECON) Pub Date : 2012-07-25 DOI: 10.1109/NAECON.2012.6531060

D. Walter, K. Bryan, J. Stephens, C. Bullmaster, V. Chakravarthy

引用次数: 7

Image fusion of the Terahertz-visual NAECON Grand Challenge data 太赫兹视觉NAECON大挑战数据的图像融合

2012 IEEE National Aerospace and Electronics Conference (NAECON) Pub Date : 2012-07-25 DOI: 10.1109/NAECON.2012.6531058

Erik Blasch, Zheng Liu, D. Petkie, R. Ewing, G. Pomrenke, K. Reinhardt

引用次数: 20

Anaylsis of motion estimation using multiple reference frames in MPEG-4AVC/H.264 MPEG-4AVC/H.264中使用多参考帧的运动估计分析

2012 IEEE National Aerospace and Electronics Conference (NAECON) Pub Date : 2012-07-25 DOI: 10.1109/NAECON.2012.6531051

J. P. Skeans, E. Balster, W. Turri

引用次数: 0

Automatic object recognition applied to Where's Waldo 自动对象识别应用于Where's Waldo

2012 IEEE National Aerospace and Electronics Conference (NAECON) Pub Date : 2012-07-25 DOI: 10.1109/NAECON.2012.6531040

T. Buchenroth, F. Garber, B. Gowker, S. Hartzell

引用次数: 0

A programmable charger for monitoring and control of multi-cell lithium-ion batteries 用于监测和控制多节锂离子电池的可编程充电器

2012 IEEE National Aerospace and Electronics Conference (NAECON) Pub Date : 2012-07-25 DOI: 10.1109/NAECON.2012.6531031

Abdullah Al-Refai, R. Abousleiman, O. Rawashdeh

{"title":"A programmable charger for monitoring and control of multi-cell lithium-ion batteries","authors":"Abdullah Al-Refai, R. Abousleiman, O. Rawashdeh","doi":"10.1109/NAECON.2012.6531031","DOIUrl":"https://doi.org/10.1109/NAECON.2012.6531031","url":null,"abstract":"Lithium-Ion batteries are becoming the favorable selection for most portable electronics and more recently electric and hybrid-electric vehicles. This is mainly due to their high energy density and low self-discharge rate. On the other hand, lithium-ion batteries require supervision while charging and discharging to maintain the voltage and current within safe limits. This paper presents a real-time programmable approach to charge lithium-ion batteries with multiple cells. Mathwork's Simulink environment is used in real-time to control a current source to charge the battery. The control logic monitors the battery cells voltages that are read through an A/D converter and then calculates the desired charging current levels. The proposed system allows engineers and researchers to easily implement and test different lithium ion battery charging methods. Furthermore, the Simulink environment allows real-time monitoring and permits charging profiles to be implemented at ease. The system is demonstrated through two different charging methods. The variations of the charging current and cell voltages are presented and compared, demonstrating the flexibility of the system.","PeriodicalId":352567,"journal":{"name":"2012 IEEE National Aerospace and Electronics Conference (NAECON)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124576527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Diffusion maps for exploring electro-optical synthetic vehicle image data 用于探索光电合成车辆图像数据的扩散图

2012 IEEE National Aerospace and Electronics Conference (NAECON) Pub Date : 2012-07-25 DOI: 10.1109/NAECON.2012.6531042

J. Ramirez, O. Mendoza-Schrock

{"title":"Diffusion maps for exploring electro-optical synthetic vehicle image data","authors":"J. Ramirez, O. Mendoza-Schrock","doi":"10.1109/NAECON.2012.6531042","DOIUrl":"https://doi.org/10.1109/NAECON.2012.6531042","url":null,"abstract":"In this work, we explore low-dimensional representations of high-dimensional data derived from electro-optical synthetic vehicle images. The collection of vehicle images consists of four different vehicle models: Toyota Camry, Toyota Avalon, Toyota Tacoma, and Nissan Sentra. This data contains 3,601 160 × 213 gray-scale vehicle images sampled uniformly over a camera view hemisphere. We use the non-linear manifold learning technique of diffusion maps with Gaussian kernel to explore low-dimensional structure the high-dimensional cloud of vehicle image observations. Diffusion maps have been shown to be a valuable tool in the analysis of high-dimensional data and the technique is able to extract an approximation for the underlying structure inherent to the data. Our analysis includes examining how the diffusion time and kernel width leads to different low-dimensional representations and we present a novel technique to relate the kernel width to the distribution of data in the observation space. In addition, we present initial results for multi-class vehicle classification through low-dimensional embedding coordinates and the out-of-sample extension of unlabeled vehicle images.","PeriodicalId":352567,"journal":{"name":"2012 IEEE National Aerospace and Electronics Conference (NAECON)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126791725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6