Example of Cognitive Computation format
Recent searches

Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format
Sample paper formatted on SciSpace - SciSpace
This content is only for preview purposes. The original open access content can be found here.
Look Inside
Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format Example of Cognitive Computation format
Sample paper formatted on SciSpace - SciSpace
This content is only for preview purposes. The original open access content can be found here.
open access Open Access
recommended Recommended

Cognitive Computation — Template for authors

Publisher: Springer
Categories Rank Trend in last 3 yrs
Computer Science Applications #66 of 693 down down by 9 ranks
Cognitive Neuroscience #12 of 96 up up by 7 ranks
Computer Vision and Pattern Recognition #15 of 85 down down by 5 ranks
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 290 Published Papers | 2491 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 09/07/2020
Related journals
Insights
General info
Top papers
Popular templates
Get started guide
Why choose from SciSpace
FAQ

Related Journals

open access Open Access
recommended Recommended

Springer

Quality:  
High
CiteRatio: 8.6
SJR: 0.53
SNIP: 2.363
open access Open Access

Springer

Quality:  
High
CiteRatio: 7.9
SJR: 0.877
SNIP: 2.132
open access Open Access
recommended Recommended

Elsevier

Quality:  
High
CiteRatio: 4.8
SJR: 0.459
SNIP: 1.587

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.

8.6

5% from 2019

CiteRatio for Cognitive Computation from 2016 - 2020
Year Value
2020 8.6
2019 8.2
2018 7.1
2017 6.5
2016 4.7
graph view Graph view
table view Table view

0.86

26% from 2019

SJR for Cognitive Computation from 2016 - 2020
Year Value
2020 0.86
2019 1.165
2018 1.06
2017 0.908
2016 0.854
graph view Graph view
table view Table view

1.676

3% from 2019

SNIP for Cognitive Computation from 2016 - 2020
Year Value
2020 1.676
2019 1.62
2018 1.965
2017 1.805
2016 1.574
graph view Graph view
table view Table view

insights Insights

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

insights Insights

  • SJR of this journal has decreased by 26% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 3% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Cognitive Computation

Guideline source: View

All company, product and service names used in this website are for identification purposes only. All product names, trademarks and registered trademarks are property of their respective owners.

Use of these names, trademarks and brands does not imply endorsement or affiliation. Disclaimer Notice

Springer

Cognitive Computation

Cognitive Computation is an international, peer-reviewed, interdisciplinary journal that publishes cutting-edge articles describing original basic and applied work involving biologically-inspired computational accounts of all aspects of natural and artificial cognitive systems...... Read More

Computer Science

i
Last updated on
09 Jul 2020
i
ISSN
1866-9956
i
Impact Factor
Very High - 3.441
i
Acceptance Rate
Not provided
i
Frequency
Not provided
i
Open Access
Yes
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
i
Bibliography Name
SPBASIC
i
Citation Type
Author Year
(Blonder et al, 1982)
i
Bibliography Example
Beenakker CWJ (2006) Specular andreev reflection in graphene. Phys Rev Lett 97(6):067,007, URL 10.1103/PhysRevLett.97.067007

Top papers written in this journal

Journal Article DOI: 10.1007/S12559-014-9255-2
An Insight into Extreme Learning Machines: Random Neurons, Random Features and Kernels
Guang-Bin Huang1
03 Apr 2014 - Cognitive Computation

Abstract:

Extreme learning machines (ELMs) basically give answers to two fundamental learning problems: (1) Can fundamentals of learning (i.e., feature learning, clus- tering, regression and classification) be made without tuning hidden neurons (including biological neurons) even when the output shapes and function modeling of these ne... Extreme learning machines (ELMs) basically give answers to two fundamental learning problems: (1) Can fundamentals of learning (i.e., feature learning, clus- tering, regression and classification) be made without tuning hidden neurons (including biological neurons) even when the output shapes and function modeling of these neurons are unknown? (2) Does there exist unified frame- work for feedforward neural networks and feature space methods? ELMs that have built some tangible links between machine learning techniques and biological learning mechanisms have recently attracted increasing attention of researchers in widespread research areas. This paper provides an insight into ELMs in three aspects, viz: random neurons, random features and kernels. This paper also shows that in theory ELMs (with the same kernels) tend to outperform support vector machine and its variants in both regression and classification applications with much easier implementation. read more read less

Topics:

Extreme learning machine (62%)62% related to the paper, Feature learning (60%)60% related to the paper, Computational learning theory (59%)59% related to the paper, Semi-supervised learning (59%)59% related to the paper, Active learning (machine learning) (59%)59% related to the paper
871 Citations
Journal Article DOI: 10.1007/S12559-009-9009-8
Hyperdimensional Computing: An Introduction to Computing in Distributed Representation with High-Dimensional Random Vectors
Pentti Kanerva1
28 Jan 2009 - Cognitive Computation

Abstract:

The 1990s saw the emergence of cognitive models that depend on very high dimensionality and randomness. They include Holographic Reduced Representations, Spatter Code, Semantic Vectors, Latent Semantic Analysis, Context-Dependent Thinning, and Vector-Symbolic Architecture. They represent things in high-dimensional vectors tha... The 1990s saw the emergence of cognitive models that depend on very high dimensionality and randomness. They include Holographic Reduced Representations, Spatter Code, Semantic Vectors, Latent Semantic Analysis, Context-Dependent Thinning, and Vector-Symbolic Architecture. They represent things in high-dimensional vectors that are manipulated by operations that produce new high-dimensional vectors in the style of traditional computing, in what is called here hyperdimensional computing on account of the very high dimensionality. The paper presents the main ideas behind these models, written as a tutorial essay in hopes of making the ideas accessible and even provocative. A sketch of how we have arrived at these models, with references and pointers to further reading, is given at the end. The thesis of the paper is that hyperdimensional representation has much to offer to students of cognitive science, theoretical neuroscience, computer science and engineering, and mathematics. read more read less

Topics:

Random indexing (52%)52% related to the paper, Latent semantic analysis (52%)52% related to the paper
761 Citations
Journal Article DOI: 10.1007/S12559-015-9333-0
What are Extreme Learning Machines? Filling the Gap Between Frank Rosenblatt’s Dream and John von Neumann’s Puzzle
Guang-Bin Huang1
15 May 2015 - Cognitive Computation

Abstract:

The emergent machine learning technique—extreme learning machines (ELMs)—has become a hot area of research over the past years, which is attributed to the growing research activities and significant contributions made by numerous researchers around the world. Recently, it has come to our attention that a number of misplaced n... The emergent machine learning technique—extreme learning machines (ELMs)—has become a hot area of research over the past years, which is attributed to the growing research activities and significant contributions made by numerous researchers around the world. Recently, it has come to our attention that a number of misplaced notions and misunderstandings are being dissipated on the relationships between ELM and some earlier works. This paper wishes to clarify that (1) ELM theories manage to address the open problem which has puzzled the neural networks, machine learning and neuroscience communities for 60 years: whether hidden nodes/neurons need to be tuned in learning, and proved that in contrast to the common knowledge and conventional neural network learning tenets, hidden nodes/neurons do not need to be iteratively tuned in wide types of neural networks and learning models (Fourier series, biological learning, etc.). Unlike ELM theories, none of those earlier works provides theoretical foundations on feedforward neural networks with random hidden nodes; (2) ELM is proposed for both generalized single-hidden-layer feedforward network and multi-hidden-layer feedforward networks (including biological neural networks); (3) homogeneous architecture-based ELM is proposed for feature learning, clustering, regression and (binary/multi-class) classification. (4) Compared to ELM, SVM and LS-SVM tend to provide suboptimal solutions, and SVM and LS-SVM do not consider feature representations in hidden layers of multi-hidden-layer feedforward networks either. read more read less

Topics:

Extreme learning machine (67%)67% related to the paper, Artificial neural network (61%)61% related to the paper, Types of artificial neural networks (61%)61% related to the paper, Competitive learning (61%)61% related to the paper, Feature learning (60%)60% related to the paper
431 Citations
Journal Article DOI: 10.1007/S12559-010-9074-Z
Clustering of Gaze During Dynamic Scene Viewing is Predicted by Motion
Parag K. Mital1, Tim J. Smith2, Robin L. Hill3, John M. Henderson4
01 Mar 2011 - Cognitive Computation

Abstract:

Where does one attend when viewing dynamic scenes? Research into the factors influencing gaze location during static scene viewing have reported that low-level visual features contribute very little to gaze location especially when opposed by high-level factors such as viewing task. However, the inclusion of transient feature... Where does one attend when viewing dynamic scenes? Research into the factors influencing gaze location during static scene viewing have reported that low-level visual features contribute very little to gaze location especially when opposed by high-level factors such as viewing task. However, the inclusion of transient features such as motion in dynamic scenes may result in a greater influence of visual features on gaze allocation and coordination of gaze across viewers. In the present study, we investigated the contribution of low- to mid-level visual features to gaze location during free-viewing of a large dataset of videos ranging in content and length. Signal detection analysis on visual features and Gaussian Mixture Models for clustering gaze was used to identify the contribution of visual features to gaze location. The results show that mid-level visual features including corners and orientations can distinguish between actual gaze locations and a randomly sampled baseline. However, temporal features such as flicker, motion, and their respective contrasts were the most predictive of gaze location. Additionally, moments in which all viewers’ gaze tightly clustered in the same location could be predicted by motion. Motion and mid-level visual features may influence gaze allocation in dynamic scenes, but it is currently unclear whether this influence is involuntary or due to correlations with higher order factors such as scene semantics. read more read less

Topics:

Gaze (62%)62% related to the paper
View PDF
387 Citations
Journal Article DOI: 10.1007/S12559-016-9397-5
Three-Way Decisions and Cognitive Computing
Yiyu Yao1
15 Mar 2016 - Cognitive Computation

Abstract:

A trisecting-and-acting model explains three-way decisions (3WD) in terms of two basic tasks. One task is to divide a universal set into three pair-wise disjoint regions called a trisection or a tri-partition of the universal set. The other task is to act upon objects in one or more regions by developing appropriate strategie... A trisecting-and-acting model explains three-way decisions (3WD) in terms of two basic tasks. One task is to divide a universal set into three pair-wise disjoint regions called a trisection or a tri-partition of the universal set. The other task is to act upon objects in one or more regions by developing appropriate strategies. 3WD are a class of effective ways and heuristics commonly used in human problem solving and information processing. We argue that 3WD are built on solid cognitive foundations and offer cognitive advantages and benefits. We demonstrate the flexibility and general applicability of 3WD by using examples from across many fields and disciplines. read more read less

Topics:

Cognitive computing (56%)56% related to the paper, Heuristics (55%)55% related to the paper, Flexibility (personality) (54%)54% related to the paper, Task (project management) (52%)52% related to the paper, Information processing (52%)52% related to the paper
325 Citations
Author Pic

SciSpace is a very innovative solution to the formatting problem and existing providers, such as Mendeley or Word did not really evolve in recent years.

- Andreas Frutiger, Researcher, ETH Zurich, Institute for Biomedical Engineering

Get MS-Word and LaTeX output to any Journal within seconds
1
Choose a template
Select a template from a library of 40,000+ templates
2
Import a MS-Word file or start fresh
It takes only few seconds to import
3
View and edit your final output
SciSpace will automatically format your output to meet journal guidelines
4
Submit directly or Download
Submit to journal directly or Download in PDF, MS Word or LaTeX

(Before submission check for plagiarism via Turnitin)

clock Less than 3 minutes

What to expect from SciSpace?

Speed and accuracy over MS Word

''

With SciSpace, you do not need a word template for Cognitive Computation.

It automatically formats your research paper to Springer formatting guidelines and citation style.

You can download a submission ready research paper in pdf, LaTeX and docx formats.

Time comparison

Time taken to format a paper and Compliance with guidelines

Plagiarism Reports via Turnitin

SciSpace has partnered with Turnitin, the leading provider of Plagiarism Check software.

Using this service, researchers can compare submissions against more than 170 million scholarly articles, a database of 70+ billion current and archived web pages. How Turnitin Integration works?

Turnitin Stats
Publisher Logos

Freedom from formatting guidelines

One editor, 100K journal formats – world's largest collection of journal templates

With such a huge verified library, what you need is already there.

publisher-logos

Easy support from all your favorite tools

Cognitive Computation format uses SPBASIC citation style.

Automatically format and order your citations and bibliography in a click.

SciSpace allows imports from all reference managers like Mendeley, Zotero, Endnote, Google Scholar etc.

Frequently asked questions

1. Can I write Cognitive Computation in LaTeX?

Absolutely not! Our tool has been designed to help you focus on writing. You can write your entire paper as per the Cognitive Computation guidelines and auto format it.

2. Do you follow the Cognitive Computation guidelines?

Yes, the template is compliant with the Cognitive Computation 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 Cognitive Computation?

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 Cognitive Computation citation style.

4. Can I use the Cognitive Computation templates for free?

Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for Cognitive Computation.

5. Can I use a manuscript in Cognitive Computation that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper Cognitive Computation that you can download at the end.

6. How long does it usually take you to format my papers in Cognitive Computation?

It only takes a matter of seconds to edit your manuscript. Besides that, our intuitive editor saves you from writing and formatting it in Cognitive Computation.

7. Where can I find the template for the Cognitive Computation?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Cognitive Computation's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

8. Can I reformat my paper to fit the Cognitive Computation's guidelines?

Of course! You can do this using our intuitive editor. It's very easy. If you need help, our support team is always ready to assist you.

9. Cognitive Computation an online tool or is there a desktop version?

SciSpace's Cognitive Computation is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

10. I cannot find my template in your gallery. Can you create it for me like Cognitive Computation?

Sure. You can request any template and we'll have it setup within a few days. You can find the request box in Journal Gallery on the right side bar under the heading, "Couldn't find the format you were looking for like Cognitive Computation?”

11. What is the output that I would get after using Cognitive Computation?

After writing your paper autoformatting in Cognitive Computation, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is Cognitive Computation'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 Cognitive Computation?

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 Cognitive Computation. 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 Cognitive Computation?

The 5 most common citation types in order of usage for Cognitive Computation are:.

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

15. How do I submit my article to the Cognitive Computation?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Cognitive Computation's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download Cognitive Computation in Endnote format?

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 Cognitive Computation Endnote style according to Elsevier guidelines.

Fast and reliable,
built for complaince.

Instant formatting to 100% publisher guidelines on - SciSpace.

Available only on desktops 🖥

No word template required

Typset automatically formats your research paper to Cognitive Computation formatting guidelines and citation style.

Verifed journal formats

One editor, 100K journal formats.
With the largest collection of verified journal formats, what you need is already there.

Trusted by academicians

I spent hours with MS word for reformatting. It was frustrating - plain and simple. With SciSpace, I can draft my manuscripts and once it is finished I can just submit. In case, I have to submit to another journal it is really just a button click instead of an afternoon of reformatting.

Andreas Frutiger
Researcher & Ex MS Word user
Use this template