2015 Twenty First National Conference on Communications (NCC)最新文献_第2页

Investigation of different acoustic modeling techniques for low resource Indian language data 低资源印度语数据的不同声学建模技术研究

2015 Twenty First National Conference on Communications (NCC) Pub Date : 2015-04-16 DOI: 10.1109/NCC.2015.7084860

R. Sriranjani, B. MuraliKarthick, S. Umesh

引用次数: 4

Digital modulation classification under non-Gaussian noise using sparse signal decomposition and maximum likelihood 基于稀疏信号分解和极大似然的非高斯噪声下的数字调制分类

2015 Twenty First National Conference on Communications (NCC) Pub Date : 2015-04-16 DOI: 10.1109/NCC.2015.7084889

Madhusmita Mohanty, U. Satija, Barathram Ramkumar, M. Manikandan

{"title":"Digital modulation classification under non-Gaussian noise using sparse signal decomposition and maximum likelihood","authors":"Madhusmita Mohanty, U. Satija, Barathram Ramkumar, M. Manikandan","doi":"10.1109/NCC.2015.7084889","DOIUrl":"https://doi.org/10.1109/NCC.2015.7084889","url":null,"abstract":"In recent years, automatic signal detection and modulation classification play a vital role in the field of cognitive radio applications. The majority of the existing signals detection and classification methods assume that the received signal is contaminated by additive white Gaussian noise. Under impulsive noise condition, the performance of the traditional modulation classification methods may be degraded. Therefore, in this paper, we investigate the application of sparse signal decomposition using an overcomplete dictionary for detection and classification of digital modulation signals. The overcomplete hybrid dictionary consists of impulse waveform and sine and cosine waveform for effectively capturing morphological components of the impulse noise and deterministic modulated signals. The proposed modulation classification method includes the following steps: sparse signal decomposition (SSD) on hybrid dictionaries, modulated signal extraction, matched filtering, and maximum likelihood (ML) classification. The performance of the direct ML and SSD-based ML classification methods are tested and validated using different modulation techniques under different Gaussian and impulse noise conditions. The proposed system achieves a classification accuracy of 89 percent at 0 dB SNR and hence outperforms the direct ML method.","PeriodicalId":302718,"journal":{"name":"2015 Twenty First National Conference on Communications (NCC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133602432","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: 10

User-adaptive layer and power allocation for video multicast over wireless 无线视频组播的用户自适应层和功率分配

2015 Twenty First National Conference on Communications (NCC) Pub Date : 2015-04-16 DOI: 10.1109/NCC.2015.7084885

Rahul Jain, S. De

引用次数: 0

Analytical model for power savings in LTE networks using DRX mechanism 基于DRX机制的LTE网络节能分析模型

2015 Twenty First National Conference on Communications (NCC) Pub Date : 2015-04-16 DOI: 10.1109/NCC.2015.7084841

R. SyamaVarma, K. Sivalingam, Li-Ping Tung, Ying-Dar Lin

引用次数: 8

Design and implementation of a Multi-Terminal Channel Emulator on LTE TestBed LTE试验台多终端信道仿真器的设计与实现

2015 Twenty First National Conference on Communications (NCC) Pub Date : 2015-04-16 DOI: 10.1109/NCC.2015.7084853

K. Prahlad, B. Ramamurthi

引用次数: 4

Dynamic object localization using hand-held cameras 使用手持相机的动态对象定位

2015 Twenty First National Conference on Communications (NCC) Pub Date : 2015-04-16 DOI: 10.1109/NCC.2015.7084827

S. Gullapally, S. R. Malireddi, S. Raman

引用次数: 3

Curvature point based HMM state prediction for online handwritten assamese strokes recognition 基于曲率点的HMM状态预测在线手写阿萨姆笔画识别

2015 Twenty First National Conference on Communications (NCC) Pub Date : 2015-04-16 DOI: 10.1109/NCC.2015.7084876

S. Mandal, S. Prasanna, S. Sundaram

{"title":"Curvature point based HMM state prediction for online handwritten assamese strokes recognition","authors":"S. Mandal, S. Prasanna, S. Sundaram","doi":"10.1109/NCC.2015.7084876","DOIUrl":"https://doi.org/10.1109/NCC.2015.7084876","url":null,"abstract":"Hidden Markov Models (HMM) are used in handwritten strokes recognition task. The two design parameters of HMM are the number of states and number of mixtures in each state. There are two approaches for finding the number of states, namely, equal number of states and variable number of states. Since the shape of strokes will be different, variable number of states approach should be beneficial. This work proposes a curvature point detection based method to predict variable number of states for modeling a handwritten stroke. The proposed method selects appropriate points from a trace so that the portion between two consecutive points is modeled as an HMM state. Accordingly, based upon handwritten stroke shape complexity, the number of appropriate points selected will change and hence the number of states assigned to the corresponding stroke. In the proposed method, the number of states is proportional to the shape complexity of the given stroke as opposed to fixed in case of brute-force. The HMM based stroke recognizer consisting of 181 distinct strokes, was trained on a set of 52,977 examples collected from approximately 100 native Assamese writers. The evaluation was done on 43,828 examples collected from same users in different sessions. The experimental results demonstrate the benefits of the proposed technique over the brute-force method, especially in case of complex shape strokes.","PeriodicalId":302718,"journal":{"name":"2015 Twenty First National Conference on Communications (NCC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134432762","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: 4

Analysis of carrier aggregated OFDM signals in presence of dual band power amplifiers 双频功率放大器下载波聚合OFDM信号的分析

2015 Twenty First National Conference on Communications (NCC) Pub Date : 2015-04-16 DOI: 10.1109/NCC.2015.7084855

Priya Singhal, Parag Aggarwal, V. Bohara

引用次数: 8

Dual band dual circular ring monopole antenna 双频双环单极天线

2015 Twenty First National Conference on Communications (NCC) Pub Date : 2015-04-16 DOI: 10.1109/NCC.2015.7084833

Amrita Mardikar, R. Mohan, Mahima Arrawatia, G. Kumar

引用次数: 0

Improved acoustic modeling for automatic dysarthric speech recognition 改进声学建模，用于自动困难语音识别

2015 Twenty First National Conference on Communications (NCC) Pub Date : 2015-04-16 DOI: 10.1109/NCC.2015.7084856

R. Sriranjani, M. Reddy, S. Umesh

引用次数: 10