Guys/Experts out there,

is it possible to help me answer some of my doubts mentioned below:

1) What is the major strength and weakness of Adaptive Resonance Theory (ART-1) network as compared to other neural networks such as Multi-Layer Perceptron?
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2) State the core advantage and disadvantage of support vector machines over radial-basis function neural networks for pattern classification?
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3) State the core advantage and disadvantage of radial-basis function neural networks over Multi-Layer Perceptron?
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4) State the core advantage and disadvantage of Associative Memory networks over Multi-Layer Perceptron?
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5) State the core advantage and disadvantage of Associative Memory networks over ART-1 network?
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6) State the core advantage and disadvantage of Associative Memory networks over Stochastic neural network?
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7) State the core advantage and disadvantage of Stochastic neural networks over Hopfield network?
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8) State the core advantage and disadvantage of Multi-Layer Perceptron over Perceptron?
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Many thanks expert and hope to hear from you soon.
Really thank you.

Regards, Jimmy.