Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Weighted Mean00:57

Weighted Mean

5.6K
While taking the arithmetic, geometric, or harmonic mean of a sample data set, equal importance is assigned to all the data points. However, all the values may not always be equally important in some data sets. An intrinsic bias might make it more important to give more weightage to specific values over others.
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
5.6K
Survival Tree01:19

Survival Tree

178
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
178
Apparent Weight01:09

Apparent Weight

8.8K
True weight is the measure of the gravitational force acting on an object. However, if the object accelerates, its measured weight is different from its true weight. Similar observations can be made when the object is submerged in water. An object's weight in water is its apparent weight, which is equal to the difference between its true weight and the buoyant forces.
Consider a person standing on a bathroom scale inside an elevator. If the scale is accurate at rest, its reading equals the...
8.8K
Improving Translational Accuracy02:07

Improving Translational Accuracy

12.0K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
12.0K
Regression Toward the Mean01:52

Regression Toward the Mean

6.5K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.5K
Choosing Between z and t Distribution01:25

Choosing Between z and t Distribution

3.2K
The z and the Student t distribution estimate the population mean using the sample mean and standard deviation. However, to decide which distribution to use for a calculation, one needs to determine the sample size, the nature of the distribution, and whether the population standard deviation is known. If the population standard deviation is known and the population is normally distributed, or if the sample size is greater than 30, the z distribution is preferred. The Student t distribution is...
3.2K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Premna odorata extract exhibits anti-inflammatory activity via suppression of NLRP3 inflammasome.

Scientific reports·2026
Same author

A Bayesian network analysis of gait speed change upon transition to uneven surfaces in older adults.

The journals of gerontology. Series A, Biological sciences and medical sciences·2026
Same author

Heat-related illness and chronic obstructive pulmonary disease: causal inference using marginal structural models.

BMC public health·2026
Same author

Risk of Mortality Associated With Substance Use Disorder in Korea: A National Population-Based Study.

Journal of Korean medical science·2026
Same author

Clinical Characteristics and Risk Factors for Syphilis Among People Living With Human Immunodeficiency Virus: A Nationwide Population-Based Cohort Study in Korea.

Journal of Korean medical science·2026
Same author

Atmospheric stressors and kidney diseases.

Nature reviews. Nephrology·2026

Related Experiment Video

Updated: Oct 5, 2025

Asymmetric Walkway: A Novel Behavioral Assay for Studying Asymmetric Locomotion
08:19

Asymmetric Walkway: A Novel Behavioral Assay for Studying Asymmetric Locomotion

Published on: January 15, 2016

9.0K

Impact of Asymmetric Weight Update on Neural Network Training With Tiki-Taka Algorithm.

Chaeun Lee1, Kyungmi Noh1, Wonjae Ji1

  • 1Department of Materials Science and Engineering, Pohang University of Science and Technology, Pohang-si, South Korea.

Frontiers in Neuroscience
|January 24, 2022
PubMed
Summary

This study analyzes conductance update asymmetry in analog neural network accelerators. We found optimal asymmetry ranges for the Tiki-Taka algorithm, improving training performance and enabling efficient calibration for non-volatile memory devices.

Keywords:
Tiki-Taka algorithmanalog AI hardwaredeep learning acceleratorneural networkresistive memoryupdate asymmetry

More Related Videos

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
05:41

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

9.5K
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
09:33

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Published on: July 28, 2013

28.6K

Related Experiment Videos

Last Updated: Oct 5, 2025

Asymmetric Walkway: A Novel Behavioral Assay for Studying Asymmetric Locomotion
08:19

Asymmetric Walkway: A Novel Behavioral Assay for Studying Asymmetric Locomotion

Published on: January 15, 2016

9.0K
A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
05:41

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

9.5K
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
09:33

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Published on: July 28, 2013

28.6K

Area of Science:

  • Materials Science
  • Computer Science
  • Electrical Engineering

Background:

  • Analog neural network accelerators using non-volatile memory offer potential for high performance and efficiency.
  • Non-ideal device characteristics, particularly conductance update asymmetry, limit the practical realization of these accelerators.
  • Existing algorithms like Tiki-Taka show promise in mitigating asymmetry issues, but systematic analysis of asymmetry specifications is lacking.

Purpose of the Study:

  • To quantitatively analyze the impact of conductance update asymmetry on neural network training performance with the Tiki-Taka algorithm.
  • To identify the required asymmetry specifications for effective neural network training.
  • To develop a novel calibration method for optimizing device and network parameters.

Main Methods:

  • Systematic exploration of asymmetry and hyper-parameter space to measure classification accuracy.
  • Analysis of how asymmetry in main and auxiliary arrays influences gradient handling by the optimizer.
  • Development and application of a calibration method using interpolation and Gaussian filtering over the Tiki-Taka hyper-parameter space.

Main Results:

  • Update asymmetry in the auxiliary array influences the optimizer's consideration of previous gradients.
  • Update asymmetry in the main array affects the frequency of gradient acceptance.
  • An optimal range of asymmetry, termed 'asymmetry specification,' was identified for effective training.
  • The proposed analysis and calibration methods are applicable to spiking neural networks.

Conclusions:

  • Conductance update asymmetry significantly impacts analog neural network training, but can be managed algorithmically.
  • The Tiki-Taka algorithm, with optimized asymmetry and hyper-parameters, can achieve high neural network training performance.
  • A novel calibration method effectively identifies optimal operating points and asymmetry specifications.
  • The findings are generalizable to various neural network architectures, including spiking neural networks.