A convolution is a function defined on two functions f(.) and g(.). If the domains of these functions are continuous so that the convolution can be defined using an integral then the convolution is said to be continuous. If, on the other hand, the domaisn of the functions are discrete then the convolution would be defined as a sum and would be said to be discrete. For more information please see the wikipedia article about convolutions.
A simple continuous distribution can take any value between two other values whereas a discrete distribution cannot.
A discrete distribution is one in which the random variable can take only a limited number of values. A cumulative distribution, which can be discrete of continuous, is the sum (if discrete) or integral (if continuous) of the probabilities of all events for which the random variable is less than or equal to the given value.
I think you are going for continuous variable, as compared with discrete variables.
It is both, a bar graph can be for discrete and continuous it depends on how you set out the chart. If it is for discrete data then you have to have a gap between each bar but on a continuous bar graph they are all next to each other WITHOUT any gaps. Also another way to discover if a bar graph is discrete or continuous the dicrete graph bars are labelled individually but on a continuous they are not labelled as such; there is a scale on the bottom axis. Hope this helps who ever needs it :D
Discrete. You can't have 1.5 pregnancies. Or anything between 1 or 2. If you have had 1, your next is 2.
The difference between continuous and discrete system lies in the variables. Whereas the continuous systems have dynamic variables, the discrete system have static variables.
A simple continuous distribution can take any value between two other values whereas a discrete distribution cannot.
circular convolution is used for periodic and finite signals while linear convolution is used for aperiodic and infinite signals. In linear convolution we convolved one signal with another signal where as in circular convolution the same convolution is done but in circular pattern ,depending upon the samples of the signal
A discrete random variable (RV) can only take a selected number of values whereas a continuous rv can take infinitely many.
Analog signals are continuous while digital signals are discrete
A discrete distribution is one in which the random variable can take only a limited number of values. A cumulative distribution, which can be discrete of continuous, is the sum (if discrete) or integral (if continuous) of the probabilities of all events for which the random variable is less than or equal to the given value.
Demand schedule: a list of demand/price equivalencies. It can best be seen as a table with discrete points. Demand function: a continuous function of price-demand interaction. Main difference: schedule is discrete; function is continuous.
there is a big difference between circular and linear convolution , in linear convolution we convolved one signal with another signal where as in circular convolution the same convolution is done but in circular patteren ,depending upon the samples of the signal
A continuous variable is one that can take any value within an interval (or a set of intervals). A discrete variable is one that can only take certain values.Some further notes:* Often a discrete variable takes integer values, but that is not necessary.* Neither discrete nor continuous variables need be limited to a finite number of possible values.* Frequently, continuous variables are continuous only in principle, and the measuring instruments or recording make them discrete. Eg your height is continuous but as soon as it is recorded as 1.75 cm or 5'9", it is made discrete.
Discrete and Continuous GraphThis will be a very basic definition but understandable one A graph is discrete when one (or both) of the variables has discrete entries, its means that are entered number, without decimal part, so the graph has no continuity, the trace will be broken parts, not a single one.beside a continuous graph is a graph where both variables are continuous, it means that their field's are de Real number, so the trace it's a continuous line.Also we can differentiated because the range are points (in a discrete one) and all the numbers (in a continuous one).
The number of students is discrete. There is no number of students between 4 and 5.
discrete distribution is the distribution that can use the value of a whole number only while continuous distribution is the distribution that can assume any value between two numbers.