國立虎尾科技大學 |

Compact and Fast Machine Learning Accelerator for IoT Devices

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Compact and Fast Machine Learning Accelerator for IoT Devices/ by Hantao Huang, Hao Yu.
作者:	Huang, Hantao.
其他作者:	Yu, Hao.
面頁冊數:	IX, 149 p. 76 illus., 61 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Computational intelligence. -
電子資源:	https://doi.org/10.1007/978-981-13-3323-1
ISBN:	9789811333231

Compact and Fast Machine Learning Accelerator for IoT Devices
Huang, Hantao.

Compact and Fast Machine Learning Accelerator for IoT Devices[electronic resource] /by Hantao Huang, Hao Yu. - 1st ed. 2019. - IX, 149 p. 76 illus., 61 illus. in color.online resource. - Computer Architecture and Design Methodologies,2367-3478. - Computer Architecture and Design Methodologies,.

Computing on Edge Devices in Internet-of-things (IoT) -- The Rise of Machine Learning in IoT system -- Least-squares-solver for Shadow Neural Network -- Tensor-solver for Deep Neural Network -- Distributed-solver for Networked Neural Network -- Conclusion.

This book presents the latest techniques for machine learning based data analytics on IoT edge devices. A comprehensive literature review on neural network compression and machine learning accelerator is presented from both algorithm level optimization and hardware architecture optimization. Coverage focuses on shallow and deep neural network with real applications on smart buildings. The authors also discuss hardware architecture design with coverage focusing on both CMOS based computing systems and the new emerging Resistive Random-Access Memory (RRAM) based systems. Detailed case studies such as indoor positioning, energy management and intrusion detection are also presented for smart buildings.

ISBN: 9789811333231

Standard No.: 10.1007/978-981-13-3323-1doiSubjects--Topical Terms:

568984
Computational intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Compact and Fast Machine Learning Accelerator for IoT Devices
LDR:02371nam a22003975i 4500 001 1015166
003 DE-He213
005 20200705080144.0
007 cr nn 008mamaa
008 210106s2019 si | s |||| 0|eng d
020 $a 9789811333231 $9 978-981-13-3323-1
024 7 $a 10.1007/978-981-13-3323-1 $2 doi
035 $a 978-981-13-3323-1
050 4 $a Q342
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.3 $2 23
100 1 $a Huang, Hantao. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1309316
245 1 0 $a Compact and Fast Machine Learning Accelerator for IoT Devices $h [electronic resource] / $c by Hantao Huang, Hao Yu.
250 $a 1st ed. 2019.
264 1 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2019.
300 $a IX, 149 p. 76 illus., 61 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Computer Architecture and Design Methodologies, $x 2367-3478
505 0 $a Computing on Edge Devices in Internet-of-things (IoT) -- The Rise of Machine Learning in IoT system -- Least-squares-solver for Shadow Neural Network -- Tensor-solver for Deep Neural Network -- Distributed-solver for Networked Neural Network -- Conclusion.
520 $a This book presents the latest techniques for machine learning based data analytics on IoT edge devices. A comprehensive literature review on neural network compression and machine learning accelerator is presented from both algorithm level optimization and hardware architecture optimization. Coverage focuses on shallow and deep neural network with real applications on smart buildings. The authors also discuss hardware architecture design with coverage focusing on both CMOS based computing systems and the new emerging Resistive Random-Access Memory (RRAM) based systems. Detailed case studies such as indoor positioning, energy management and intrusion detection are also presented for smart buildings.
650 0 $a Computational intelligence. $3 568984
650 0 $a Microprocessors. $3 632481
650 0 $a Mathematical optimization. $3 527675
650 1 4 $a Computational Intelligence. $3 768837
650 2 4 $a Processor Architectures. $3 669787
650 2 4 $a Optimization. $3 669174
700 1 $a Yu, Hao. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 891333
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9789811333224
776 0 8 $i Printed edition: $z 9789811333248
830 0 $a Computer Architecture and Design Methodologies, $x 2367-3478 $3 1269988
856 4 0 $u https://doi.org/10.1007/978-981-13-3323-1
912 $a ZDB-2-INR
912 $a ZDB-2-SXIT
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)
950 $a Intelligent Technologies and Robotics (R0) (SpringerNature-43728)