One commonly argued disadvantage of a divide-and-conquer approach is that recursion is slow: the overhead of the repeated subroutine calls, along with that of storing the call stack (the state at each point in the recursion), can outweigh any advantages of the approach. This, however, depends upon the implementation style: with large enough recursive base cases, the overhead of recursion can become negligible for many problems. Another problem of a divide-and-conquer approach is that, for simple problems, it may be more complicated th ...

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Divide and conquer algorithm, Divide and conquer algorithm - Implementation, Divide and conquer algorithm - Variations, Divide and conquer algorithm - Advantages, Divide and conquer algorithm - Solving difficult problems, Divide and conquer algorithm - Algorithm efficiency, Divide and conquer algorithm - Parallelism, Divide and conquer algorithm - Memory access, Divide and conquer algorithm - Disadvantages

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The video game light gun is typically modeled on a ballistic weapon (usually a pistol) and is used for targeting objects on a video screen. With force feedback, the light gun can also simulate the recoil of the weapon. Light guns are very popular in arcade games, but have never caught on in the home video game console market after the NES, SEGA and SNES systems. This may be because people are reluctant to buy more than one extra controller for their system, let alone a special-purpose and often expensive peripheral, or because light guns are less satisfactory to use with the small television screens in peoples h ...

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Light gun, Light gun - Light guns in video games, Light gun - How light guns work, Light gun - Method one, Light gun - Method two, Light gun - Combining the methods, Light gun - Detection, Light gun - Positional guns, Light gun - Notable home console games with light gun support

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Dynamic-link library - Delphi. In the heading of a source file, the keyword library is used instead of program. In the end of the file, the functions to be exported are listed in exports clause. Delphi does not require LIB files to import functions from DLLs. To link to a DLL, external keyword is used in function declaration ...

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Dynamic-link library, Dynamic-link library - Background, Dynamic-link library - Features, Dynamic-link library - Memory management, Dynamic-link library - Symbol resolution and binding, Dynamic-link library - Explicit run-time linking, Dynamic-link library - Compiler and language considerations, Dynamic-link library - Delphi, Dynamic-link library - Microsoft Visual Basic, Dynamic-link library - C and C++, Dynamic-link library - Programming examples

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The original show was hosted by veteran radio and television newsman John Daly. Panelist Bennett Cerf often referred to him as John Charles Daly, Daly's professional name at the start of his CBS News career in Washington. (As writer Joe Persico noted in his 1988 biography of Edward R. Murrow, Daly shortened his name at the request of CBS Vice President Ed Klauber, but the JCD name had lingered on among some listeners and viewers.) Sometimes Cerf would introduce Daly by ...

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What's My Line?, What's My Line? - Hosts and panelists, What's My Line? - Game play, What's My Line? - Standard rounds, What's My Line? - Mystery guest rounds, What's My Line? - Style of the show, What's My Line? - Alternate versions, What's My Line? - Versions in the United States, What's My Line? - Versions around the world, What's My Line? - Show trivia, What's My Line? - Related pages

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The simplest brute force algorithm for independent set simply examines every vertex subset of size at least k and checks whether it is an independent set. This is polynomial time if k equals the number of vertices, or if is a constant less than this, but not if it's, say, half the number of vertices. A much easier problem to solve is that of finding a maximal independent set, which is an independent set not contained in any other independent set. We begin with a single vertex. We find a vertex not adjacent to it a ...

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Independent set problem, Independent set problem - Description, Independent set problem - Algorithms, Independent set problem - Proof of NP-completeness

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In arcades, positional guns are fairly commonplace. A positional gun appears as a gun mounted to the cabinet on a swivel that allows for aiming. These are often confused with light guns but work quite differently. These guns may not be removed from the cabinet like the optical counterparts, which are tethered and stored in a mounted holster. They are typically more expensive initially but easier to maintain and repair. Games that use positional guns include the popular Operation Wolf, Space Gun and Terminator 2: Judgment Day (although, o ...

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Light gun, Light gun - Light guns in video games, Light gun - How light guns work, Light gun - Method one, Light gun - Method two, Light gun - Combining the methods, Light gun - Detection, Light gun - Positional guns, Light gun - Notable home console games with light gun support

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The following examples show language specific bindings for exporting symbols from DLLs. [Delphi] library Example; // Function that adds two numbers function AddNumbers(a, b: Double): Double; cdecl; begin AddNumbers := a + b end; // Export this function exports AddNumbers; // DLL initialization code: no special handling needed begin end. [C and C++] #include <windows.h> // Export this function extern "C" __declspec(dllexport) double AddNumbers(double a, double b); // DLL initializati ...

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Dynamic-link library, Dynamic-link library - Background, Dynamic-link library - Features, Dynamic-link library - Memory management, Dynamic-link library - Symbol resolution and binding, Dynamic-link library - Explicit run-time linking, Dynamic-link library - Compiler and language considerations, Dynamic-link library - Delphi, Dynamic-link library - Microsoft Visual Basic, Dynamic-link library - C and C++, Dynamic-link library - Programming examples

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Insertion sort is very similar to bubble sort. In bubble sort, after k passes through the array, the k largest elements have bubbled to the top. (Or the k smallest elements have bubbled to the bottom, depending on which way you do it.) In insertion sort, after k passes through the array, you have a run of k sorted elements at the bottom of the array. Each pass inserts another element into the sorted run. So with bubble sort, each pass takes less time than the previous one, but with insert ...

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Insertion sort, Insertion sort - Good and bad input cases, Insertion sort - Variants, Insertion sort - Comparisons to other sorts, Insertion sort - Implementations, Insertion sort - C, Insertion sort - Haskell

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The various algorithms can be classified by the number of patterns each uses. String searching algorithm - Single pattern algorithms. Let m be the length of the pattern and let n be the length of the searchable text. String searching algorithm - Algorithms using finite set of patterns. Aho-Corasick algorithm String searching algorithm - Algorithms using infinite number of patterns. Naturally, the patterns can not be enumerated in this case. They ...

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String searching algorithm, String searching algorithm - Basic classification, String searching algorithm - Single pattern algorithms, String searching algorithm - Algorithms using finite set of patterns, String searching algorithm - Algorithms using infinite number of patterns, String searching algorithm - Other classification, String searching algorithm - Naïve string search, String searching algorithm - Index methods

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The complexity class P is the set of decision problems that can be solved by a deterministic machine in polynomial time. This class corresponds to an intuitive idea of the problems which can be effectively solved in the worst cases. The complexity class NP is the set of decision problems that can be solved by a non-deterministic machine in polynomial time. This class contains many problems that people would like to be able to solve effectively, including the Boolean satisfiability problem, the Hamiltonian path problem and the Vertex cover problem. All the problems in this cl ...

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Computational complexity theory, Computational complexity theory - Overview, Computational complexity theory - Decision problems, Computational complexity theory - Complexity classes, Computational complexity theory - The P = NP question, Computational complexity theory - Intractability, Computational complexity theory - Notable researchers

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The question of whether P is the same set as NP is the most important open question in theoretical computer science. There is even a $1,000,000 prize for solving it. (See complexity classes P and NP and oracles). Questions like this motivate the concepts of hard and complete. A set of problems X is hard for a set of problems Y if every problem in Y can be transformed easily into some problem in X with the same answer. The definition of "easily" is different in different contexts. ...

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Computational complexity theory, Computational complexity theory - Overview, Computational complexity theory - Decision problems, Computational complexity theory - Complexity classes, Computational complexity theory - The P = NP question, Computational complexity theory - Intractability, Computational complexity theory - Notable researchers

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Problems that are solvable in theory, but can't be solved in practice, are called intractable. What can be solved "in practice" is open to debate, but in general only problems that have polynomial-time solutions are solvable for more than the smallest inputs. Problems that are known to be intractable include those that are EXPTIME-complete. If NP is not the same as P, then the NP-complete problems are also intractable. To see why exponential-time solutions are not usable in practice, consider a problem that requires 2nSee also:

Computational complexity theory, Computational complexity theory - Overview, Computational complexity theory - Decision problems, Computational complexity theory - Complexity classes, Computational complexity theory - The P = NP question, Computational complexity theory - Intractability, Computational complexity theory - Notable researchers

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Much of complexity theory deals with decision problems. A decision problem is a problem where the answer is always YES/NO. For example, the problem IS-PRIME is: given an integer written in binary, return whether it is a prime number or not. A decision problem is equivalent to a language, which is a set of finite-length strings. For a given decision problem, the equivalent language is the set of all strings for which the answer is YES. Decision problems are often considered because an arbitrary problem can always be reduc ...

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Computational complexity theory, Computational complexity theory - Overview, Computational complexity theory - Decision problems, Computational complexity theory - Complexity classes, Computational complexity theory - The P = NP question, Computational complexity theory - Intractability, Computational complexity theory - Notable researchers

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ADCs are integral to much current music reproduction technology, since much music production is done on computers; even when analog recording is used, an ADC is still needed to create the PCM data stream that goes onto a compact disc. The current crop of AD converters utilized in music can sample at rates up to 192 kilohertz. Many people in the business consider this an overkill and pure marketing hype, due to the Nyquist-Shannon sampling theorem. Simply put, they say the analog waveform does not have enough information in it to neces ...

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Analog-to-digital converter, Analog-to-digital converter - Resolution, Analog-to-digital converter - Response type, Analog-to-digital converter - Linear ADCs, Analog-to-digital converter - Non-linear ADCs, Analog-to-digital converter - Accuracy, Analog-to-digital converter - Sampling rate, Analog-to-digital converter - Aliasing, Analog-to-digital converter - Dither, Analog-to-digital converter - Oversampling, Analog-to-digital converter - ADC structures, Analog-to-digital converter - Application to music recording, Analog-to-digital converter - Other applications

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All ADCs work by sampling their input at discrete intervals of time. Their output is therefore an incomplete picture of the behaviour of the input. There is no way of knowing, by looking at the output, what the input was doing between one sampling instant and the next. If the input is known to be changing slowly compared to the sampling rate, then it can be assumed that the value of the signal between two sample instants was somewhere between the two sampled values. If, however, the input signal is changing fast compare ...

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Analog-to-digital converter, Analog-to-digital converter - Resolution, Analog-to-digital converter - Response type, Analog-to-digital converter - Linear ADCs, Analog-to-digital converter - Non-linear ADCs, Analog-to-digital converter - Accuracy, Analog-to-digital converter - Sampling rate, Analog-to-digital converter - Aliasing, Analog-to-digital converter - Dither, Analog-to-digital converter - Oversampling, Analog-to-digital converter - ADC structures, Analog-to-digital converter - Application to music recording, Analog-to-digital converter - Other applications

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In A to D converters, performance can be improved using dither. This is a very small amount of random noise (white noise) which is added to the input before conversion. Its amplitude is set to be about half of the least significant bit. Its effect is to cause the state of the LSB to randomly oscillate between 0 and 1 in the presence of very low levels of input, rather than sticking at a fixed value. Rather than the signal simply getting cut off altogether at this low level (which is only being quantized to a resolution of 1 bit), it extends ...

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Analog-to-digital converter, Analog-to-digital converter - Resolution, Analog-to-digital converter - Response type, Analog-to-digital converter - Linear ADCs, Analog-to-digital converter - Non-linear ADCs, Analog-to-digital converter - Accuracy, Analog-to-digital converter - Sampling rate, Analog-to-digital converter - Aliasing, Analog-to-digital converter - Dither, Analog-to-digital converter - Oversampling, Analog-to-digital converter - ADC structures, Analog-to-digital converter - Application to music recording, Analog-to-digital converter - Other applications

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Video games have to split their very limited computing time between several tasks. This added to the limited resources of the programmers, the less strict goals of believable (and not necessarily exact) simulation and (perhaps most importantly) the real-time requirement have combined in such a way that video games, for the most part, have used relatively primitive collision detection algorithms, alt ...

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Collision detection, Collision detection - Overview, Collision detection - Collision detection in physical simulation, Collision detection - A posteriori vs a priori, Collision detection - n-body pruning, Collision detection - Temporal coherence, Collision detection - Physically based temporal coherence, Collision detection - Pairwise pruning, Collision detection - Exact pairwise collision detection, Collision detection - A priori collision detection, Collision detection - Spatial partitioning miscellanea, Collision detection - Collision detection in video games, Collision detection - Collision detection in computational geometry

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Because of the many important problems in this class, there have been extensive efforts to find algorithms that decide the problems in NP in time which is polynomial in the input size, which is generally considered efficient. However, there are a large number of problems in NP that defy such attempts, seeming to require superpolynomial time. Whether these problems really aren't solvable in polynomial time is one of the greatest open questions in computer scie ...

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NP complexity, NP complexity - Introduction and applications, NP complexity - Why some NP problems are hard to solve, NP complexity - Other characterizations, NP complexity - Example

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The analog signal is continuous in time and it is necessary to convert this to a flow of digital values. It is therefore required to define the rate at which new digital values are sampled from the analog signal. The rate of new values is called the sampling rate or sampling frequency of the converter. A continuously varying bandlimited signal can be sampled (that is, the signal values at intervals of time T, the sampling time, are measured and stored) and then the original signal can be exactly reproduced from th ...

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Analog-to-digital converter, Analog-to-digital converter - Resolution, Analog-to-digital converter - Response type, Analog-to-digital converter - Linear ADCs, Analog-to-digital converter - Non-linear ADCs, Analog-to-digital converter - Accuracy, Analog-to-digital converter - Sampling rate, Analog-to-digital converter - Aliasing, Analog-to-digital converter - Dither, Analog-to-digital converter - Oversampling, Analog-to-digital converter - ADC structures, Analog-to-digital converter - Application to music recording, Analog-to-digital converter - Other applications

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In an informed search, a heuristic that is specific to the problem is used as a guide. A good heuristic will make an informed search dramatically out-perform any uninformed search. There are few prominent informed list-search algorithms. A possible member of that category is a hash table with a hashing function that is a heuristic based on the problem at hand. Most informed search algorithms explore trees. These include Best-first search, and A*. Like the uninformed algorith ...

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Search algorithm, Search algorithm - Uninformed search, Search algorithm - List search, Search algorithm - Tree search, Search algorithm - Graph search, Search algorithm - Informed search, Search algorithm - Adversarial search, Search algorithm - Constraint satisfaction, Search algorithm - Other types

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Divide-and-conquer algorithms are naturally implemented as recursive procedures. In that case, the partial sub-problems leading to the one currently being solved are implicitly stored in the procedure call stack. However, D&C solutions can also be implemented by a non-recursive algorithm that stores the partial sub-problems in some explicit data structure, such as a stack, queue, or priority queue. This approach allows more freedom in the choice of the sub-problem that is to be solved next, a feature that is important in some applications — e.g. in breadth-first recur ...

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Divide and conquer algorithm, Divide and conquer algorithm - Implementation, Divide and conquer algorithm - Variations, Divide and conquer algorithm - Advantages, Divide and conquer algorithm - Solving difficult problems, Divide and conquer algorithm - Algorithm efficiency, Divide and conquer algorithm - Parallelism, Divide and conquer algorithm - Memory access, Divide and conquer algorithm - Disadvantages

Read more here: » Divide and conquer algorithm: Encyclopedia II - Divide and conquer algorithm - Implementation