Linear search of input states. In contrast, the output from combinational logic is purely a combination of its present inputs, unaffected by the previous input and output states. These logic circuits are known as computer memory. They vary in performance, based on factors of speed, complexity, and reliability of storage, and many different types of designs are used based on the application. Three-state logic gates. A three-state logic gate is a type of logic gate that can have three different outputs: high (H), low (L) and high-impedance (Z). The high-impedance state plays no role in the logic, which 	Logic gate
17827816	is strictly binary. These devices are used on buses of the CPU to allow multiple chips to send data. A group of three-states driving a line with a suitable control circuit is basically equivalent to a multiplexer, which may be physically distributed over separate devices or plug-in cards. In electronics, a high output would mean the output is sourcing current from the positive power terminal (positive voltage). A low output would mean the output is sinking current to the negative power terminal (zero voltage). High impedance would mean that the output is effectively disconnected from the circuit. Manufacturing	Logic gate
17827817	. Since the 1990s, most logic gates are made in CMOS (complementary metal oxide semiconductor) technology that uses both NMOS and PMOS transistors. Often millions of logic gates are packaged in a single integrated circuit. Early techniques. Non-electronic implementations are varied, though few of them are used in practical applications. Many early electromechanical digital computers, such as the Harvard Mark I, were built from relay logic gates, using electro-mechanical relays. Logic gates can be made using pneumatic devices, such as the Sorteberg relay or mechanical logic gates, including on a molecular scale. Logic gates have been made out of 	Logic gate
17827818	DNA (see DNA nanotechnology) and used to create a computer called MAYA (see MAYA-II). Logic gates can be made from quantum mechanical effects, see quantum logic gate. Photonic logic gates use nonlinear optical effects. In principle any method that leads to a gate that is functionally complete (for example, either a NOR or a NAND gate) can be used to make any kind of digital logic circuit. Note that the use of 3-state logic for bus systems is not needed, and can be replaced by digital multiplexers, which can be built using only simple logic gates (such as 	Logic gate
17827819	NAND gates, NOR gates, or AND and OR gates). Logic families. There are several logic families with different characteristics (power consumption, speed, cost, size) such as: RDL (resistor–diode logic), RTL (resistor-transistor logic), DTL (diode–transistor logic), TTL (transistor–transistor logic) and CMOS. There are also sub-variants, e.g. standard CMOS logic vs. advanced types using still CMOS technology, but with some optimizations for avoiding loss of speed due to slower PMOS transistors. Logic gate A logic gate is an idealized model of computation or a physical electronic device implementing a Boolean function, a logical operation performed on one 	Logic gate
17827820	Linear search Linear search In computer science, a linear search or sequential search is a method for finding an element within a list. It sequentially checks each element of the list until a match is found or the whole list has been searched. A linear search runs in at worst linear time and makes at most comparisons, where is the length of the list. If each element is equally likely to be searched, then linear search has an average case of comparisons, but the average case can be affected if the search probabilities for each element vary. Linear search is rarely practical 	Linear search
17827821	because other search algorithms and schemes, such as the binary search algorithm and hash tables, allow significantly faster searching for all but short lists. Algorithm. A linear search sequentially checks each element of the list until it finds an element that matches the target value. If the algorithm reaches the end of the list, the search terminates unsuccessfully. Basic algorithm. Given a list of elements with values or records , and target value , the following subroutine uses linear search to find the index of the target in . With a sentinel. The basic algorithm above makes two comparisons per iteration: one to 	Linear search
17827822	check if equals T", and the other to check if still points to a valid index of the list. By adding an extra record to the list (a sentinel value) that equals the target, the second comparison can be eliminated until the end of the search, making the algorithm faster. The search will reach the sentinel if the target is not contained within the list. In an ordered table. If the list is ordered such that , the search can establish the absence of the target more quickly by concluding the search once exceeds the target. This variation requires a sentinel  that is greater than the target. Analysis. For a list with "n" items, the best case is when the value is equal to the first element of the list, in which case only one comparison is needed. The worst case is when the value is not in the list (or occurs only once at the end of the list), in which case "n" comparisons are needed. If the value being sought occurs "k" times in the list, and all orderings of the list are equally likely, the expected number of comparisons is For example, if the value being sought occurs  once in the list, and all orderings of the list are equally likely, the expected number of comparisons is formula_2. However, if it is "known" that it occurs once, then at most "n" - 1 comparisons are needed, and the expected number of comparisons is (for example, for "n" = 2 this is 1, corresponding to a single if-then-else construct). Either way, asymptotically the worst-case cost and the expected cost of linear search are both O("n"). Non-uniform probabilities. The performance of linear search improves if the desired value is more likely to be near the beginning of  the list than to its end. Therefore, if some values are much more likely to be searched than others, it is desirable to place them at the beginning of the list. In particular, when the list items are arranged in order of decreasing probability, and these probabilities are geometrically distributed, the cost of linear search is only O(1). Application. Linear search is usually very simple to implement, and is practical when the list has only a few elements, or when performing a single search in an un-ordered list. When many values have to be searched in the same list , it often pays to pre-process the list in order to use a faster method. For example, one may sort the list and use binary search, or build an efficient search data structure from it. Should the content of the list change frequently, repeated re-organization may be more trouble than it is worth. As a result, even though in theory other search algorithms may be faster than linear search (for instance binary search), in practice even on medium-sized arrays (around 100 items or less) it might be infeasible to use anything else. On larger arrays, it only makes  sense to use other, faster search methods if the data is large enough, because the initial time to prepare (sort) the data is comparable to many linear searches. Linear search In computer science, a linear search or sequential search is a method for finding an element within a list. It sequentially checks each element of the list until a match is found or the whole list has been searched. A linear search runs in at worst linear time and makes at most comparisons, where is the length of the list. If each element is equally likely to be searched, then