Search the courses, subjects, tracks, games and features, or jump straight to a page.
Learn it your way
A short class with Sarah and her students. The other ways are under More.
Sign up free to listen. Transcripts are free to read.
Today, we'll discuss how to count bit strings that contain the substring '000'. Does anyone know what a bit string is?
Isn't it just a sequence of 0s and 1s?
Exactly! A bit string can be made up of any combination of 0s and 1s. Now, why do we care about the substring '000'?
Because it might appear multiple times in longer strings!
Good point! Our goal is to determine how many bit strings of a certain length contain '000'.
How do we even start with that?
One efficient method is to count the total number of bit strings and then subtract those that do not contain '000'. We call those 'bad' strings.
What’s the total number of bit strings of length n?
"Great question! There are 2^n possible bit strings for length n. So, we can express this as...
We classify our bad strings into three categories. Can anyone guess what they could be?
Maybe starting with '1'?
Correct! If a string starts with '1', the remaining bits can also be any combination that doesn't create '000'. That counts as A(n-1) bad strings. What about the next category?
What about starting with '01'? That should lead to A(n-2) bad strings, right?
Exactly right! Lastly, what happens if a string starts with '00'?
Then the next bit has to be '1'... and it would leave A(n-3)!
"Spot on! Now we can combine that into a single recurrence for bad strings:
To proceed with our recurrence relation, we need initial conditions. Can anyone tell me what A(1) would be?
For length of 1, the only valid strings are '0' and '1', so A(1) = 2.
Exactly! And what about A(2)?
That would be '00', '01', '10', and '11' — four strings, so A(2) = 4.
Great! Now, how many strings do we have for A(3)?
For length 3, we have: '000', '001', '010', '011', '100', '101', '110', '111', so A(3) = 7.
Awesome! Now that we have A(1), A(2), and A(3), we can substitute these values into our recurrence and calculate counts for larger strings.
In real life, where could knowing these counts be beneficial?
In data encoding, where patterns must be evaluated!
Also in error-checking algorithms to ensure valid sequences!
Absolutely! To recap, we’ve learned that by classifying strings into bad and total, we can find efficient ways to count substrings. Any last questions?
Can we visualize this using a tree diagram?
Great idea! That would be an excellent way to see how each string develops and connects. Let's work on that in the next session.
Term
What is a bit string?
Click to flip
Term
Define A(n)
Click to flip
This section discusses the recurrence relations for counting bit strings of length n containing the substring '000' by considering the complementary case of strings not containing '000'.
In this section, bit strings of a specified length that contain the substring '000' are analyzed through the creation of recurrence relations. The approach involves counting the total bit strings and subtracting those that do not contain '000', while employing logical categories to form a recurrence for the 'bad' strings.
This section delves into the problem of determining how many bit strings of length n contain the substring '000'. Instead of directly counting those strings, a more practical method is used by finding the count of 'bad' strings — strings that do not have the substring '000'. We denote the number of bit strings of length n containing '000' as B(n) and the number of bad strings as A(n). The relationship posits that:
Where 2^n represents all possible bit strings of length n. The section further categorizes bad strings into three distinct types based on their starting sequences, leading to the formation of a recurrence relation for A(n):
n-1 bits for bad strings).n-2 bits for bad strings).n-3 bits).Each category is analyzed for its contributions to the total count of bad strings:
This equation is of degree 3, necessitating three initial conditions (A(1), A(2), A(3)) to be specified. Once these values are established, the recurrence relation can be solved to derive the counts of strings containing '000' for any desired length n. The beauty of this approach lies in the understanding of combinatorial structures governing bit generation and substring inclusion.