Search

نمایش تعداد 1-10 از 11

Massive labeled solar image data benchmarks for automated feature recognition

نوع: Conference Paper

نویسنده : Schuh, Michael A.; Angryk, Rafal A.

ناشر: IEEE

سال: 2014

Towards a Multi-tenancy Aware Cloud Service Composition

نوع: Conference Paper

نویسنده : Sellami, W. , Kacem, H.H. , Kacem, A.H.

ناشر: IEEE

سال: 2014

Cloud Computing in Amazon and Microsoft Azure platforms: Performance and service comparison

نوع: Conference Paper

نویسنده : Dordevic, Borislav S.; Jovanovic, Slobodan P.; Timcenko, Valentina V.

ناشر: IEEE

سال: 2014

Secure Transmission With Antenna Selection in MIMO Nakagami- <inline-formula> <img src="/images/tex/254.gif" alt="m"> </inline-formula> Fading Channels

نوع: Journal Paper

نویسنده : Lifeng Wang; Elkashlan, M.; Jing Huang; Schober, Robert; Mallik, Ranjan K.

ناشر: IEEE

سال: 2014

Generalized Diversity Reception in the Presence of Multiple Distinct Interferers: An Outage Performance Analysis

نوع: Journal Paper

نویسنده : Miridakis, Nikolaos /I/.; Vergados, Dimitrios D.

ناشر: IEEE

سال: 2014

A Low Complexity Antenna Switching for Joint Wireless Information and Energy Transfer in MIMO Relay Channels

نوع: Journal Paper

نویسنده : Krikidis, Ioannis; Sasaki, Seishi; Timotheou, Stelios; Zhiguo Ding

ناشر: IEEE

سال: 2014

An MGF-Based Unified Framework to Determine the Joint Statistics of Partial Sums of Ordered i.n.d. Random Variables

نوع: Journal Paper

نویسنده : Sung Sik Nam; Hong-Chuan Yang; Alouini, Mohamed-Slim; Dong In Kim

ناشر: IEEE

سال: 2014

Vibration-based wireless machine condition monitoring system

نوع: Conference Paper

نویسنده : Ikram, Waqas; Chen, Su-Liang; Harvei, Trygve; Olsen, Thomas; Mikalsen, Espen; Svoen, Geir; Froystein, Sverre; Myhre, Bard

ناشر: IEEE

سال: 2014

Dynamic pre-training of Deep Recurrent Neural Networks for predicting environmental monitoring data

نوع: Conference Paper

نویسنده : Ong, Bun Theang; Sugiura, Komei; Zettsu, Koji

ناشر: IEEE

سال: 2014

On the effectiveness of energy-aware real-time scheduling algorithms on single-core platforms

نوع: Conference Paper

نویسنده : Bambagini, Mario; Bertogna, Marko; Buttazzo, Giorgio

ناشر: IEEE

سال: 2014

Search

Massive labeled solar image data benchmarks for automated feature recognition

Towards a Multi-tenancy Aware Cloud Service Composition

Cloud Computing in Amazon and Microsoft Azure platforms: Performance and service comparison

Secure Transmission With Antenna Selection in MIMO Nakagami- <inline-formula> <img src="/images/tex/254.gif" alt="m"> </inline-formula> Fading Channels

Generalized Diversity Reception in the Presence of Multiple Distinct Interferers: An Outage Performance Analysis

A Low Complexity Antenna Switching for Joint Wireless Information and Energy Transfer in MIMO Relay Channels

An MGF-Based Unified Framework to Determine the Joint Statistics of Partial Sums of Ordered i.n.d. Random Variables

Vibration-based wireless machine condition monitoring system

Dynamic pre-training of Deep Recurrent Neural Networks for predicting environmental monitoring data

On the effectiveness of energy-aware real-time scheduling algorithms on single-core platforms

نویسنده

ناشر

سال

کلیدواژه

نوع

زبان

نوع محتوا

عنوان ناشر

Search

Filters

Massive labeled solar image data benchmarks for automated feature recognition

Towards a Multi-tenancy Aware Cloud Service Composition

Cloud Computing in Amazon and Microsoft Azure platforms: Performance and service comparison

Secure Transmission With Antenna Selection in MIMO Nakagami- <inline-formula> <img src="/images/tex/254.gif" alt="m"> </inline-formula> Fading Channels

Generalized Diversity Reception in the Presence of Multiple Distinct Interferers: An Outage Performance Analysis

A Low Complexity Antenna Switching for Joint Wireless Information and Energy Transfer in MIMO Relay Channels

An MGF-Based Unified Framework to Determine the Joint Statistics of Partial Sums of Ordered i.n.d. Random Variables

Vibration-based wireless machine condition monitoring system

Dynamic pre-training of Deep Recurrent Neural Networks for predicting environmental monitoring data

On the effectiveness of energy-aware real-time scheduling algorithms on single-core platforms