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Related Concept Videos

Classification of Signals01:30

Classification of Signals

In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
Stereotype Content Model02:16

Stereotype Content Model

The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence categorization, a person will feel...
Classification of Systems-II01:31

Classification of Systems-II

Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
Classification of Systems-I01:26

Classification of Systems-I

Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
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Force Classification01:22

Force Classification

Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
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Encoding01:19

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Related Experiment Video

Updated: Jun 8, 2026

Creating Objects and Object Categories for Studying Perception and Perceptual Learning
14:38

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

The contextually controlled, feature-mediated classification of symbols.

Pamela DeRosse1, Lanny Fields

  • 1The Zucker Hillside Hospital of the North Shore LIJ Health System, Glen Oaks, NY 11004, USA. pdrosse@lij.edu

Journal of the Experimental Analysis of Behavior
|October 2, 2010
PubMed
Summary

This study explored how people classify arbitrary symbols using contextual cues and learned features. Results show that while some participants successfully classify symbols based on context, others do not, highlighting conditions for complex classification.

Keywords:
acquired features of symbolscollege studentscontextual controlhierarchical classificationkeyboard respondingstimulus equivalence

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Generating Strictly Controlled Stimuli for Figure Recognition Experiments
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Generating Strictly Controlled Stimuli for Figure Recognition Experiments

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Area of Science:

  • Cognitive Psychology
  • Behavioral Science

Background:

  • Human classification abilities are often based on learned features and contextual cues.
  • Understanding how these classification repertoires are established is crucial for explaining complex cognitive processes.

Purpose of the Study:

  • To investigate the establishment of complex classification repertoires using arbitrary stimuli.
  • To examine the role of contextual cues and acquired features in symbol classification.

Main Methods:

  • An experiment using arbitrary stimuli without pre-existing associations.
  • Employed an ABA reversal design to assess classification consistency.
  • Tested 4 participants with varying classification behaviors.

Main Results:

  • Two participants formed equivalence classes based on context and features.
  • One participant's classification depended on the presence of contextual cues.
  • One participant deviated from predicted classification, and another focused solely on features, ignoring context.

Conclusions:

  • Contextual cues and acquired features are critical for establishing complex classification repertoires.
  • Individual differences exist in how effectively people utilize context and features for classification.
  • The findings provide insights into the conditions underlying naturalistic classification behaviors.