Example of IEEE Journal on Emerging and Selected Topics in Circuits and Systems format
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Example of IEEE Journal on Emerging and Selected Topics in Circuits and Systems format Example of IEEE Journal on Emerging and Selected Topics in Circuits and Systems format Example of IEEE Journal on Emerging and Selected Topics in Circuits and Systems format Example of IEEE Journal on Emerging and Selected Topics in Circuits and Systems format Example of IEEE Journal on Emerging and Selected Topics in Circuits and Systems format Example of IEEE Journal on Emerging and Selected Topics in Circuits and Systems format Example of IEEE Journal on Emerging and Selected Topics in Circuits and Systems format
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Example of IEEE Journal on Emerging and Selected Topics in Circuits and Systems format Example of IEEE Journal on Emerging and Selected Topics in Circuits and Systems format Example of IEEE Journal on Emerging and Selected Topics in Circuits and Systems format Example of IEEE Journal on Emerging and Selected Topics in Circuits and Systems format Example of IEEE Journal on Emerging and Selected Topics in Circuits and Systems format Example of IEEE Journal on Emerging and Selected Topics in Circuits and Systems format Example of IEEE Journal on Emerging and Selected Topics in Circuits and Systems format
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open access Open Access

IEEE Journal on Emerging and Selected Topics in Circuits and Systems — Template for authors

Publisher: IEEE
Categories Rank Trend in last 3 yrs
Electrical and Electronic Engineering #80 of 693 down down by 4 ranks
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 231 Published Papers | 1871 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 02/06/2020
Related journals
Insights
General info
Top papers
Popular templates
Get started guide
Why choose from SciSpace
FAQ

Related Journals

open access Open Access

IEEE

Quality:  
High
CiteRatio: 6.4
SJR: 0.786
SNIP: 2.027
open access Open Access

IEEE

Quality:  
High
CiteRatio: 3.7
SJR: 0.396
SNIP: 1.133
open access Open Access
recommended Recommended

IEEE

Quality:  
High
CiteRatio: 9.7
SJR: 1.652
SNIP: 1.947

Journal Performance & Insights

CiteRatio

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

A measure of average citations received per peer-reviewed paper published in the journal.

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

8.1

16% from 2019

CiteRatio for IEEE Journal on Emerging and Selected Topics in Circuits and Systems from 2016 - 2020
Year Value
2020 8.1
2019 7.0
2018 6.7
2017 6.0
2016 5.7
graph view Graph view
table view Table view

0.868

5% from 2019

SJR for IEEE Journal on Emerging and Selected Topics in Circuits and Systems from 2016 - 2020
Year Value
2020 0.868
2019 0.826
2018 0.723
2017 0.619
2016 0.568
graph view Graph view
table view Table view

1.808

2% from 2019

SNIP for IEEE Journal on Emerging and Selected Topics in Circuits and Systems from 2016 - 2020
Year Value
2020 1.808
2019 1.775
2018 1.826
2017 1.763
2016 1.783
graph view Graph view
table view Table view

insights Insights

  • CiteRatio of this journal has increased by 16% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

insights Insights

  • SJR of this journal has increased by 5% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 2% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

IEEE Journal on Emerging and Selected Topics in Circuits and Systems

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IEEE

IEEE Journal on Emerging and Selected Topics in Circuits and Systems

Approved by publishing and review experts on SciSpace, this template is built as per for IEEE Journal on Emerging and Selected Topics in Circuits and Systems formatting guidelines as mentioned in IEEE author instructions. The current version was created on 02 Jun 2020 and has been used by 287 authors to write and format their manuscripts to this journal.

Engineering

i
Last updated on
02 Jun 2020
i
ISSN
2156-3357
i
Impact Factor
High - 1.793
i
Open Access
No
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
i
Bibliography Name
IEEEtran
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Citation Type
Numbered
[25]
i
Bibliography Example
C. W. J. Beenakker, “Specular andreev reflection in graphene,” Phys. Rev. Lett., vol. 97, no. 6, p.

Top papers written in this journal

Journal Article DOI: 10.1109/JETCAS.2013.2243032
Design of a WSN Platform for Long-Term Environmental Monitoring for IoT Applications

Abstract:

The Internet of Things (IoT) provides a virtual view, via the Internet Protocol, to a huge variety of real life objects, ranging from a car, to a teacup, to a building, to trees in a forest. Its appeal is the ubiquitous generalized access to the status and location of any “thing” we may be interested in. Wireless sensor netwo... The Internet of Things (IoT) provides a virtual view, via the Internet Protocol, to a huge variety of real life objects, ranging from a car, to a teacup, to a building, to trees in a forest. Its appeal is the ubiquitous generalized access to the status and location of any “thing” we may be interested in. Wireless sensor networks (WSN) are well suited for long-term environmental data acquisition for IoT representation. This paper presents the functional design and implementation of a complete WSN platform that can be used for a range of long-term environmental monitoring IoT applications. The application requirements for low cost, high number of sensors, fast deployment, long lifetime, low maintenance, and high quality of service are considered in the specification and design of the platform and of all its components. Low-effort platform reuse is also considered starting from the specifications and at all design levels for a wide array of related monitoring applications. read more read less

Topics:

Wireless sensor network (55%)55% related to the paper, The Internet (52%)52% related to the paper, Key distribution in wireless sensor networks (51%)51% related to the paper, Functional design (50%)50% related to the paper
544 Citations
open accessOpen access Journal Article DOI: 10.1109/JETCAS.2019.2910232
Eyeriss v2: A Flexible Accelerator for Emerging Deep Neural Networks on Mobile Devices
Yu-Hsin Chen1, Tien-Ju Yang1, Joel Emer1, Vivienne Sze1

Abstract:

A recent trend in deep neural network (DNN) development is to extend the reach of deep learning applications to platforms that are more resource and energy-constrained, e.g., mobile devices. These endeavors aim to reduce the DNN model size and improve the hardware processing efficiency and have resulted in DNNs that are much ... A recent trend in deep neural network (DNN) development is to extend the reach of deep learning applications to platforms that are more resource and energy-constrained, e.g., mobile devices. These endeavors aim to reduce the DNN model size and improve the hardware processing efficiency and have resulted in DNNs that are much more compact in their structures and/or have high data sparsity . These compact or sparse models are different from the traditional large ones in that there is much more variation in their layer shapes and sizes and often require specialized hardware to exploit sparsity for performance improvement. Therefore, many DNN accelerators designed for large DNNs do not perform well on these models. In this paper, we present Eyeriss v2, a DNN accelerator architecture designed for running compact and sparse DNNs. To deal with the widely varying layer shapes and sizes, it introduces a highly flexible on-chip network, called hierarchical mesh, that can adapt to the different amounts of data reuse and bandwidth requirements of different data types, which improves the utilization of the computation resources. Furthermore, Eyeriss v2 can process sparse data directly in the compressed domain for both weights and activations and therefore is able to improve both processing speed and energy efficiency with sparse models. Overall, with sparse MobileNet, Eyeriss v2 in a 65-nm CMOS process achieves a throughput of 1470.6 inferences/s and 2560.3 inferences/J at a batch size of 1, which is $12.6\times $ faster and $2.5\times $ more energy-efficient than the original Eyeriss running MobileNet. read more read less

Topics:

Sparse matrix (51%)51% related to the paper, Deep learning (51%)51% related to the paper
527 Citations
open accessOpen access Journal Article DOI: 10.1109/JETCAS.2018.2885981
Emerging MPEG Standards for Point Cloud Compression

Abstract:

Due to the increased popularity of augmented and virtual reality experiences, the interest in capturing the real world in multiple dimensions and in presenting it to users in an immersible fashion has never been higher. Distributing such representations enables users to freely navigate in multi-sensory 3D media experiences. U... Due to the increased popularity of augmented and virtual reality experiences, the interest in capturing the real world in multiple dimensions and in presenting it to users in an immersible fashion has never been higher. Distributing such representations enables users to freely navigate in multi-sensory 3D media experiences. Unfortunately, such representations require a large amount of data, not feasible for transmission on today’s networks. Efficient compression technologies well adopted in the content chain are in high demand and are key components to democratize augmented and virtual reality applications. Moving Picture Experts Group, as one of the main standardization groups dealing with multimedia, identified the trend and started recently the process of building an open standard for compactly representing 3D point clouds, which are the 3D equivalent of the very well-known 2D pixels. This paper introduces the main developments and technical aspects of this ongoing standardization effort. read more read less

Topics:

Standardization (51%)51% related to the paper
View PDF
470 Citations
Journal Article DOI: 10.1109/JETCAS.2012.2187106
Design Optimization and Implementation for RF Energy Harvesting Circuits
Prusayon Nintanavongsa1, Ufuk Muncuk1, David Richard Lewis1, Kaushik R. Chowdhury1

Abstract:

A new design for an energy harvesting device is proposed in this paper, which enables scavenging energy from radiofrequency (RF) electromagnetic waves. Compared to common alternative energy sources like solar and wind, RF harvesting has the least energy density. The existing state-of-the-art solutions are effective only over ... A new design for an energy harvesting device is proposed in this paper, which enables scavenging energy from radiofrequency (RF) electromagnetic waves. Compared to common alternative energy sources like solar and wind, RF harvesting has the least energy density. The existing state-of-the-art solutions are effective only over narrow frequency ranges, are limited in efficiency response, and require higher levels of input power. This paper has a twofold contribution. First, we propose a dual-stage energy harvesting circuit composed of a seven-stage and ten-stage design, the former being more receptive in the low input power regions, while the latter is more suitable for higher power range. Each stage here is a modified voltage multiplier, arranged in series and our design provides guidelines on component choice and precise selection of the crossover operational point for these two stages between the high (20 dBm) and low power (-20 dBm) extremities. Second, we fabricate our design on a printed circuit board to demonstrate how such a circuit can run a commercial Mica2 sensor mote, with accompanying simulations on both ideal and non-ideal conditions for identifying the upper bound on achievable efficiency. With a simple yet optimal dual-stage design, experiments and characterization plots reveal approximately 100% improvement over other existing designs in the power range of -20 to 7 dBm. read more read less

Topics:

Integrated circuit design (56%)56% related to the paper, Energy harvesting (55%)55% related to the paper, Voltage multiplier (53%)53% related to the paper, Electrical efficiency (53%)53% related to the paper, Electronic circuit (52%)52% related to the paper
View PDF
444 Citations
Journal Article DOI: 10.1109/JETCAS.2016.2547718
Recent Progress in Phase-Change Memory Technology
IBM1

Abstract:

We survey progress in the PCM field over the past five years, ranging from large-scale PCM demonstrations to materials improvements for high–temperature retention and faster switching. Both materials and new cell designs that support lower-power switching are discussed, as well as higher reliability for long cycling endurance... We survey progress in the PCM field over the past five years, ranging from large-scale PCM demonstrations to materials improvements for high–temperature retention and faster switching. Both materials and new cell designs that support lower-power switching are discussed, as well as higher reliability for long cycling endurance. Two paths towards higher density are discussed: through 3D integration by the combination of PCM and 3D-capable access devices, and through multiple bits per cell, by understanding and managing resistance drift caused by structural relaxation of the amorphous phase. We also briefly survey work in the nascent field of brain-inspired neuromorphic systems that use PCM to implement non-Von Neumann computing. read more read less

Topics:

Phase-change memory (56%)56% related to the paper
302 Citations
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IEEE Journal on Emerging and Selected Topics in Circuits and Systems format uses IEEEtran citation style.

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Frequently asked questions

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Yes, the template is compliant with the IEEE Journal on Emerging and Selected Topics in Circuits and Systems guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in IEEE Journal on Emerging and Selected Topics in Circuits and Systems?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the IEEE Journal on Emerging and Selected Topics in Circuits and Systems citation style.

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12. Is IEEE Journal on Emerging and Selected Topics in Circuits and Systems's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for IEEE Journal on Emerging and Selected Topics in Circuits and Systems?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for IEEE Journal on Emerging and Selected Topics in Circuits and Systems. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In IEEE Journal on Emerging and Selected Topics in Circuits and Systems?

The 5 most common citation types in order of usage for IEEE Journal on Emerging and Selected Topics in Circuits and Systems are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

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Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in IEEE Journal on Emerging and Selected Topics in Circuits and Systems Endnote style according to Elsevier guidelines.

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