Perceptron

Any neural network that uses perceptron rule in training is called perceptron neural network. It was suggested by Frank Rosenblatt in 1960 which is popularly used for solving the separable problem. It uses the perceptron learning rule while updating the weight that is, wij(new) = wij (old) + η ei xi. where ei xi= error and η = learning rate. Perceptron is mainly used in pattern recognition even though they have lots of other capabilities as well. The two types of perceptron are single layer perceptron and multi-layer perceptron. A single layer neural network that uses a perceptron learning rule and basically is used for solving linearly separable problems is referred to single layer perceptron. Multi-layer perceptron is a multi-layer neural network which uses perceptron rule with back propagation algorithm in training that is basically used for solving complex and non-linear problems.

Summary

Any neural network that uses perceptron rule in training is called perceptron neural network. It was suggested by Frank Rosenblatt in 1960 which is popularly used for solving the separable problem. It uses the perceptron learning rule while updating the weight that is, wij(new) = wij (old) + η ei xi. where ei xi= error and η = learning rate. Perceptron is mainly used in pattern recognition even though they have lots of other capabilities as well. The two types of perceptron are single layer perceptron and multi-layer perceptron. A single layer neural network that uses a perceptron learning rule and basically is used for solving linearly separable problems is referred to single layer perceptron. Multi-layer perceptron is a multi-layer neural network which uses perceptron rule with back propagation algorithm in training that is basically used for solving complex and non-linear problems.

Things to Remember

  • Any neural network that uses perceptron rule in training is called perceptron neural network. It was suggested by Frank Rosenblatt in 1960 which is popularly used for solving the separable problem.
  • It uses the perceptron learning rule while updating the weight that is, wij(new) = wij (old) + η ei xi. where ei xi= error and η = learning rate.
  • Perceptron is mainly used in pattern recognition even though they have lots of other capabilities as well.
  • The two types of perceptron are single layer perceptron and multi layer perceptron.
  • A single layer neural network that uses a perceptron learning rule and basically is used for solving linearly separable problems is referred to single layer perceptron.
  • Multi-layer perceptron is a multi-layer neural network which uses perceptron rule with back propagation algorithm in training that is basically used for solving complex and non-linear problems.

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Subjective Questions

Q1:

Define Erosion of the cervix and list its causes ?


Type: Short Difficulty: Easy

Show/Hide Answer
Answer: <p><strong>Erosion of the cervix</strong></p>
<p>It is a condition in which the central columnar epithelium protrudes out through the external OS of the cervix, onto the vaginal portion of the cervix. It is also known as ectropion.</p>
<p>Causes</p>
<ol>
<li>Contracting chronic infection</li>
<li>Unusual Ph balance</li>
<li>Increased in estrogen level</li>
<li>Trauma</li>
</ol>

Q2:

List the measures of treatment and also write the ways to prevent it ?


Type: Short Difficulty: Easy

Show/Hide Answer
Answer: <p>Treatment</p>
<ol>
<li>Diathermy</li>
<li>Cryocautery</li>
<li>Infection prevention by use of prophylactic antibiotics</li>
<li>Post- operative advice</li>
</ol>
<p>Prevention</p>
<p>1. Raise the foot end of the bed and keep the patient warm</p>
<p>2. Give oxygen as per as patient need</p>
<p>3. Give IM pethidine 100 mg and diazepam 10 mg</p>
<p>4. Encourage to patient to do blood test (haemoglobin, grouping, cross match)</p>
<p>5. Start Iv infusion with 5% dextrose to maintain hydration</p>
<p>6. Transfuse the blood according to need</p>

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Perceptron

Perceptron

Perceptron

Any neural network that uses perceptron rule in training is called perceptron neural network. It was suggested by Frank Rosenblatt in 1960 which is popularly used for solving the separable problem.

.

The activation function is defined as,

.

It uses the perceptron learning rule while updating the weight that is,

wij(new) = wij (old) + η ei xi.

where ei xi= error,

η = learning rate.

Perceptron is mainly used in pattern recognition even though they have lots of other capabilities as well. The two types of perceptron are presented below:

  1. Single layer perceptron: A single layer neural network that uses a perceptron learning rule and basically is used for solving linearly separable problems is referred to single layer perceptron.
  2. Multi-layer perceptron: It is a multi-layer neural network which uses perceptron rule with back propagation algorithm in training that is basically used for solving complex and non-linear problems.

References:

  1. Elaine Rich, Kevin Knight 1991, "Artificial Intelligence".
  2. Nilsson, Nils J. Principles of Artificial Intelligence, Narosa Publishing House New Delhi, 1998.
  3. Norvig, Peter & Russel, Stuart Artificial Intelligence: A modern Approach, Prentice Hall, NJ, 1995
  4. Patterson, Dan W. Introduction to Artificial Intelligence and Expert Systems, Prentice Hall of India Private Limited New Delhi, 1998.

Lesson

Applications of AI

Subject

Computer Engineering

Grade

Engineering

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