Memory is an integral part of a computer system. It's primary function is to store all information required by the system. Typically, a memory unit holds programs and data. A computer designer has to pay attention to the memory unit design, since the memory system cost is a significant fraction of the cost of total system. The system performances largely dependent on the oganization, is storage capacity, and speed of operation of the memory system.
Friday, 31 May 2013
what is the difference between direct and indirect instruction ?
Thursday, 30 May 2013
What is Probability Density Function ?
Probability Density Function-The range of possible values is uncountably infnite for continuous random variables. So in this case, the distribution is defined by the probability density function f (x) for the given range of random variable X.
The probability density function f(x), is a function which, when integated a and b gives the probability that the random variable will assume a value between a and b.
Key Features of a Von Neumann Machine
Key Features of a Von Neumann Machine:
》The Von Neumann machine uses stored program concept.The program and data are stored in the same unit. The computers prior to this used to store programs and data in separate memories. Entering and modifying these programs were very difficult as they were entered manually.
》Each location of the memoy can be addressed independently.
》Execution of instruction in Von Neumann machine is carried out in a sequential fashion (unless explicitly altered by the program itself from one instruction to the next.
Thursday, 23 May 2013
What is Discrete veriate ?
If a random variable takes a finite set of values, it is called a discrete variate, and if it assumes an infinite number ofuncountable values, it is called a continuous variate.
What is Discrete Distribution ?
Discrete Distribution-if a real variable X be associated with the outcome of a random experiment then since the values which X takes depend on chance it is said to be a random variable or a stechastic variable or variate.
Probability Mass Function
Probability Mass Function-
In probability theory and statistics, a probability mass function (p.m.f) is a function that gives the probability that a discrete random variable is exactly equal ot some value. The probability mass function is often the primay means of defning a discrete probability distribution, and such functions exist for either scalar or multivariate random variables, given that the distribution is discrete.
A probability mass function differs from a probability density function (p.d.f) in that the latter is associated with continuous rather than discrete andom variables; the values ofthe latter are not probabilities as such: a p.d.f must be integrated over an interval to yield a probability.