Answer: None; all will be recoverable
Explanation:
If a signal (band-limited) is sampled at regular intervals, it could be recoverable or not, based on the number of samples taken.
Let's assume that we want to take samples of a simple sinusoid; If we take more than two samples during a signal cycle, the original waveform will be able to be reconstructed, just passing the sampled waveform through a low-pass filter.
In the more general case in which the signal occupies a frequency spectrum, if the sample frequency is greater than the double of the highest frequency in the spectrum, the signal can be retrieved completely, according to the Nyquist Theorem.
In this case , as the highest frequency is 145 Hz, it would be enough to take samples at a rate greater than 290 Hz; As the sample rate is 295 Hz, all the signal can be recovered, at least, using an ideal "brickwall" low-pass filter.
Answer:
Option 4 is the correct answer to the above question.
Explanation:
In the Linux operating system, The etc folder is listed on the root directory. When any user wants to go in the root directory of the Linux operating system from anywhere, then he needs to follow the command of the name of the folder where he wants to go with the '/' symbols. The above question states that the user wants to go to the etc folder of the root directory, then he needs to press the command '/etc' with the help of cd command because cd command is used to open any folder. So the option 4 is the correct, while the other is not because--
- Option 1 states about cd which gives the error.
- Option 2 states about cd /home/mary/etc which take the user to the etc folder which is in the mary folder.
- Option 3 states about the cd etc which is used to take the user on the etc folder which is in the current folder.
- Option 5 states about the cd\etc which gives the error.
Answer:
Greedy is an algorithmic paradigm that builds up a solution piece by piece, always choosing the next piece that offers the most obvious and immediate benefit. Greedy algorithms are used for optimization problems. An optimization problem can be solved using Greedy if the problem has the following property: At every step, we can make a choice that looks best at the moment, and we get the optimal solution of the complete problem.
If a Greedy Algorithm can solve a problem, then it generally becomes the best method to solve that problem as the Greedy algorithms are in general more efficient than other techniques like Dynamic Programming. But Greedy algorithms cannot always be applied. For example, the Fractional Knapsack problem (See this) can be solved using Greedy, but 0-1 Knapsack cannot be solved using Greedy.
The following are some standard algorithms that are Greedy algorithms.
1) Kruskal’s Minimum Spanning Tree (MST): In Kruskal’s algorithm, we create an MST by picking edges one by one. The Greedy Choice is to pick the smallest weight edge that doesn’t cause a cycle in the MST constructed so far.
2) Prim’s Minimum Spanning Tree: In Prim’s algorithm also, we create an MST by picking edges one by one. We maintain two sets: a set of the vertices already included in MST and the set of the vertices not yet included. The Greedy Choice is to pick the smallest weight edge that connects the two sets.
3) Dijkstra’s Shortest Path: Dijkstra’s algorithm is very similar to Prim’s algorithm. The shortest-path tree is built up, edge by edge. We maintain two sets: a set of the vertices already included in the tree and the set of the vertices not yet included. The Greedy Choice is to pick the edge that connects the two sets and is on the smallest weight path from source to the set that contains not yet included vertices.
4) Huffman Coding: Huffman Coding is a loss-less compression technique. It assigns variable-length bit codes to different characters. The Greedy Choice is to assign the least bit length code to the most frequent character. The greedy algorithms are sometimes also used to get an approximation for Hard optimization problems. For example, the Traveling Salesman Problem is an NP-Hard problem. A Greedy choice for this problem is to pick the nearest unvisited city from the current city at every step. These solutions don’t always produce the best optimal solution but can be used to get an approximately optimal solution.
Answer:
The act of operation without direct control by a person.
Explanation:
The encyclopedia describes automation as “the procedure of producing an equipment, a method, or an arrangement function automatically.” We describe automation as "the formulation and utilization of technology to observe and regulate the reproduction and distribution of products and assistance.” to the society.
