Recent content by the_amateur

Given a square matrix A, the condition that characterizes an eigenvalue, λ, is the existence of a nonzero vector x such that A x = λ x; this equation can be rewritten as follows: Ax=\lambda x (A-\lambda )x = 0 (A-\lambda I )x = 0 -------------------- 1 After the above...

first of all i think you should get a good book on probability since most of the problems posted by you are quite basic and you seem to be guessing the answers.. in this question given is P(A) = 0.7 P(B) = 0.4 P(A^{c}\capB^{c})= 0.1 you have to find P(A\capB) use...

your answer is wrong.. use bayes theorem

your answer is wrong i don think it is a dependent event the probability of a person with heart attack is 0.7 so the probability that among 4 at least 1 has heart attack = 1 - probability that none have = 1...

The answer is y[n] = (\frac{2}{3})^{n}U[n]

@Larrytsai you mentioned the following where x(t) can be any input signal. You say that in the system that i have posted the system is stable since x(t) is stable but i find by intuition that this is not the case if the input signal has discontinuities. At the point of discontinuity the...

thanks again!

Thanks for your reply but i am trying to find if it is stable or not. i think my derivation is wrong.

Thanks for the answer! I guess here k_{i} indicates the number of wavelengths of x_{i}(t) in the time period T of x(t).So it has to be an integer as only then x(t) can be periodic. Please correct me if i am wrong.

The book states that if the mean \bar{x}=\sum_{i=1}^{n}x_{i}/n Then for another distribution which is related as y_{i}=ax_{i}+b the mean is \bar{y}=a\bar{x}+b what they are trying to imply here is that by properly choosing 'a' and 'b' the process of finding mean can be simplified...

What is the condition for the continuous time signal x(t) to be periodic if it is the linear combination of n periodic signals. where x(t) = a_{1}x_{1}(t)+a_{2}x_{2}(t)+a_{3}x_{3}(t)+......a_{n}x_{n}(t) where x_{i}(t) is periodic with fundamental period T_{i} \forall i, where i \in...

Is the following system stable. If so how. y(t)= \frac{d}{dt} x(t)I have tried the following proof but i think it is wrong. PROOF: The System is LINEAR The system is time invariant So on applying the stability criterion for LTI systems ie . \int^{\infty}_{-\infty} h(t) dt < \infty...

A proof of the above statement would be more helpful.