neural network. Information in the network is coded in terms of variation in the sequence of all-or-none (spike) events, or temporal patterns, transmitted between artificial "neurons". Identifying the nonlinear input/output properties of neurons involved in forming memories for new patterns and developing mathematical models of those nonlinear properties enable the identification of specific types of sounds. These neural networks can then be trained as "recognizers" of a target sound, like a gunshot, even in the presence of high noise. Regardless of the methods used to isolate gunfire from other impulsive sounds or infrared sensing, standard triangulation methods can be used to locate the source of the gunshot once it has been recognized as a gunshot. Optical discriminating had previously consisted of methods, among them spatial, spectral, and creative temporal filters, to eliminate solar glint as a false alarm. Earlier sensors could not operate at speeds fast enough to allow for the incorporation of matched temporal filters that now eliminate solar glint as a false alarm contributor. Architectures Different system architectures have different capabilities and are used for specific applications. In general there are 2 architectures: stand-alone systems with local microphone arrays, and distributed sensor arrays (“wide-area acoustic surveillance”). The former are generally used for immediate detection and alerting to a nearby shooter in the vicinity of the system; such uses are typically used to help protect soldiers, military vehicles and craft, and also to protect small open-space areas (e.g., parking lot, park). The latter are used for protecting large areas such as cities, municipalities, critical infrastructure, transportation hubs, and military operating bases. Most stand-alone systems have been designed for military use where the goal is immediately alerting human targets so they may take evasive and/or neutralization action. Such systems generally consist of a small array of microphones separated by a precise small distance. Each microphone hears the sounds of gunfire at minute differences in time, allowing the system to calculate the range and bearing of the origin of the gunfire relative to the system. Military systems generally rely on both the muzzle blast and projectile shockwave “snap” sounds to validate their classification of gunfire and to calculate the range to the origin. Distributed sensor arrays have a distinct advantage over stand-alone systems in that they can successfully classify gunfire with and without hearing a projectile “snap” sound, even amid heavy background noise and echoes. Such systems are the accepted norm