Design a Hopfield Network for 4-bit bipolar patterns. The training patterns are
S1 = [1 1 -1 -1]
S2 = [ -1 1 -1 1]
S3 = [ -1 -1 -1 1]
Find the weight matrix and energy for the three input samples. Determine the pattern to which the sample S = [−1 1 −1 −1]associates.
To design a Hopfield Network for the given 4-bit bipolar patterns, we will: 1. Compute the Weight Matrix (W) using the Hebbian learning rule. 2. Compute the Energy Function (E) for the given input samples. 3. Determine the pattern to which S = [-1 1 -1 -1] associates. --- _________ ________ _____ ______ _____ __________ ___ ______ ________ _____.
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पृष्ठ x²+2y² = 1 पर फलन f(x, y) = x² + y के चरम मान ज्ञात कीजिए।
अस्पष्ट फलन प्रमेय की सहायता से यह दिखाइए कि 1 के प्रतिवेश में एक ऐसा अवकलनीय फलन g होता है, जिससे कि (2,1) के प्रतिवेश में g (1) = 2 और F(g(y), y) = 0 जहाँ
से फलन F परिभाषित है। g' (y) भी ज्ञात कीजिए।
द्विशः समाकलन का प्रयोग करके दीर्घवृत्तज का आयतन ज्ञात कीजिए।
Consider a Kohonen self-organizing net (given below) with two cluster units and five input units. The weight vectors for the cluster units are given by
w1 = { 3.0,5.0,7.0,9.0,0.1 }
w2 = { 0.1,9.0,7.0,5.0,3.0 }
Use the square of the Euclidean distance to find the winning cluster unit for the input pattern (x)
x = [ 0.0 5.0 0.1 5.0 0.0 ]
Using learning rate of 0.25, find the new weights for the winning unit.
- List the elements of the following sets described by rule method:
- A ={n Î N : n is odd prime less than 200}
- B = {x ÎR : x 2 - 9x +18 = 0}
- C ={max{a, b}: a, b are twin primes £ 200}
Using max-min composition, find the relation between R and S:
z = 1 और 2 = x² + y² से परिबद्ध ठोस घनाकृति का द्रव्यमान ज्ञात कीजिए, जबकि घनत्व फलन्, 8(x, y, z) = |x| हो।