Floating-gate in the context of Neural network

Semiconductor memory is a digital electronic semiconductor device used for digital data storage, such as computer memory. It typically refers to devices in which data is stored within metal–oxide–semiconductor (MOS) memory cells on a silicon integrated circuit memory chip. There are numerous different types using different semiconductor technologies. The two main types of random-access memory (RAM) are static RAM (SRAM), which uses several transistors per memory cell, and dynamic RAM (DRAM), which uses a transistor and a MOS capacitor per cell. Non-volatile memory (such as EPROM, EEPROM and flash memory) uses floating-gate memory cells, which consist of a single floating-gate transistor per cell.

Most types of semiconductor memory have the property of random access, which means that it takes the same amount of time to access any memory location, so data can be efficiently accessed in any random order. This contrasts with data storage media such as CDs which read and write data consecutively and therefore the data can only be accessed in the same sequence it was written. Semiconductor memory also has much faster access times than other types of data storage; a byte of data can be written to or read from semiconductor memory within a few nanoseconds, while access time for rotating storage such as hard disks is in the range of milliseconds. For these reasons it is used for primary storage, to hold the program and data the computer is currently working on, among other uses.

Non-volatile memory (NVM) or non-volatile storage is a type of computer memory that can retain stored information even after power is removed. In contrast, volatile memory needs constant power in order to retain data.

Non-volatile memory typically refers to storage in memory chips, which store data in floating-gate memory cells consisting of floating-gate MOSFETs (metal–oxide–semiconductor field-effect transistors), including flash memory storage such as NAND flash and solid-state drives (SSD).