公开(公告)号：KR1020130122340A

公开(公告)日：2013-11-07

申请号：KR1020120045593

申请日：2012-04-30

Applicant: 목포대학교산학협력단

Inventor： 이우용 ,  최명수 ,  박희만 ,  맹세영 ,  박상혁 ,  정민아 ,  이연우 ,  이성로

IPC: H04W40/22 ,  H04W84/18

CPC classification number: G05D1/0259 ,  H04L45/20 ,  H04W84/18

Abstract: The present invention is a method for autonomously driving a mobile node through a wireless sensor network, and the mobile node is able to autonomously drive by interacting with neighboring sensor nodes without help of a map manufactured in advance, a compass or a GPS device. Furthermore, the mobile node uses an ANHC value obtained by periodically averaging the hop number of 1-hop neighboring nodes, moves toward the ANHC value lessens and finally reaches a destination. An autonomous driving method in the present invention does not require localization of a mobile node, the application limit of existing autonomous driving algorithms and costly effective autonomous driving of a mobile node is possible. [Reference numerals] (AA) Destination;(BB) Departure place

Abstract translation: 本发明是一种通过无线传感器网络自主地驱动移动节点的方法，并且移动节点能够通过与相邻传感器节点交互而自主地驱动，而无需预先制造的映射，罗盘或GPS设备的帮助。 此外，移动节点使用通过周期性地平均1跳相邻节点的跳数获得的ANHC值，朝向ANHC值移动并最终到达目的地。 本发明的自主驾驶方法不需要移动节点的定位，现有的自主驾驶算法的应用限制和移动节点的昂贵的有效自主驾驶是可能的。 （参考号）（AA）目的地;（BB）出发地点

公开(公告)号：KR1020130136813A

公开(公告)日：2013-12-13

申请号：KR1020120060508

申请日：2012-06-05

Applicant: 목포대학교산학협력단

Inventor： 임정수 ,  박선 ,  이성호 ,  김진우 ,  이우용 ,  이성로

IPC: G10L19/02

Abstract: The present invention relates to a simplification method of a support vector machine-based speech and music classifier, a simplification method of a support vector machine-based speech and music classifier according to the present invention facilitates implementation of a classifier into an embedded system by reducing the amount of calculation while maintaining the performance of classification of a support vector machine (SVM)-based speech/music classifier for a selectable mode vocoder (SMV). According to the present invention is able to reduce the amount of operation which is followed by an SVM-based classifier by simplifying a support vector of the SVM-based speech/music classifier for an SMV codec, and in particular, the implementation of the classifier into an embedded system is easy. [Reference numerals] (AA) Calculating the average contribution of the support vector;(BB) Calculating the relativce contribution of the support vector;(CC) Removing the support vector having the smaller contribution compared to the threshold value

Abstract translation: 本发明涉及基于支持向量机的语音和音乐分类器的简化方法，根据本发明的基于支持向量机的语音和音乐分类器的简化方法有利于通过减少将分类器实现到嵌入式系统中 在维持用于可选模式声码器（SMV）的支持向量机（SVM）的语音/音乐分类器的分类的性能的同时计算的量。 根据本发明，通过简化用于SMV编解码器的基于SVM的语音/音乐分类器的支持向量，能够减少基于SVM的分类器所遵循的操作量，特别地，分类器的实现 嵌入式系统很容易。 （AA）计算支持向量的平均贡献;（BB）计算支持向量的相对贡献;（CC）去除与阈值相比具有较小贡献的支持向量

公开(公告)号：KR101333272B1

公开(公告)日：2013-11-27

申请号：KR1020120052607

申请日：2012-05-17

Applicant: 목포대학교산학협력단

Inventor： 이우용 ,  강세윤 ,  김태완 ,  김현산 ,  위성남 ,  정민아 ,  이연우 ,  이성로

IPC: G01S5/02

Abstract: The present invention relates a method for determining (recognizing) the position of each sensor node forming a wireless sensor network. More specifically, the present invention is about a method for recognizing a range-free position, which calculates the average number of adjacent node hops and determines the position of the sensor node based on the same, and a system using the same.

Abstract translation: 本发明涉及一种确定（识别）形成无线传感器网络的每个传感器节点的位置的方法。 更具体地说，本发明涉及一种用于识别无范围位置的方法，其计算相邻节点跳跃的平均数，并且基于该距离位置来确定传感器节点的位置，以及使用该距离的位置的系统。

公开(公告)号：KR1020130136812A

公开(公告)日：2013-12-13

申请号：KR1020120060507

申请日：2012-06-05

Applicant: 목포대학교산학협력단

Inventor： 임정수 ,  박선 ,  이성호 ,  김진우 ,  이우용 ,  이성로

IPC: G10L19/02

Abstract: The present invention relates to a support vector machine (SVM)-based speech and music classifier of a hierarchical structure for a selectable mode vocoder (SMV) codec, a SVM-based speech and music classifier according to the present invention facilitates implementation of a classifier into an embedded system by reducing the amount of operation while maintaining the classification performance of an SVM-based speech/music classifier. According to the present invention the amount of operation accompanied by an SVM-based classifier using an existing SMV codec classifier in front of the SVM-based speech/music classifier for an SMV codec, in particular, the implementation of a classifier into an embedded system is easily done.

Abstract translation: 本发明涉及一种用于可选模式声码器（SMV）编解码器的分级结构的基于支持向量机（SVM）的语音和音乐分类器，根据本发明的基于SVM的语音和音乐分类器有助于实现分类器 通过在保持基于SVM的语音/音乐分类器的分类性能的同时减少操作量而进入嵌入式系统。 根据本发明，使用SMV编解码器的基于SVM的语音/音乐分类器前面的现有SMV编解码器分类器的基于SVM的分类器的操作量，特别是将分类器实现为嵌入式系统 很容易完成