Design of A New CMOS Controllable Mixed-Signal Current Mode Fuzzy Logic Controller (FLC) Chip

Analog Gaussian Function Circuit: Architectures, Operating Principles and Applications

“…In most cases, digital or other analog circuits are attached around a partially tunable Gaussian or Gaussian-like function circuit (Figure 28) to improve the tunability of the Gaussian function curve's three characteristics (height, mean value and variance). The extra components include multiplexers (MUX) [11,81] and/or switches [15,[82][83][84][85] and other digital circuitry (mixed-mode architectures [86]) [82][83][84], series of resistors [19,87,88], DACs [22,28,87] or Analog to Digital converters (ADC) [22], multipliers [28,31,33,87] or tunable current mirrors [89,90], OTAs [91][92][93][94] or other amplifiers [12,87], common mode feedback circuits (CMFB) [22,95], squarers [33], exponentiators [87], current-controlled current-conveyor second generation (CCII) circuits [90], minimum value circuits [96] and additional current correlators [97]. Four representative examples are provided in Figures 29-32.…”

“…... Each implementation uses the extra components differently, but the general concept regarding the added extra components is to enhance the operation of a simple Gaussian function core, for example, to provide variance tunability to the circuit. In particular, multiplexers and switches are used to select the appropriate value from multiple parallel outputs in order to achieve the tunability in the variance [11,15,[81][82][83][84][85]. In a similar manner, the series of resistors alter the Gaussian function output by changing the total resistance value [19,87,88].…”

“…Most of them are mixed-mode implementations which took advantage of both analog and digital circuits. The existing categories include controllers [72,74,79,80,85,88], object recognition inference [82][83][84] or neural perception [31] engines or processors [22], function approximators [71,75] and a min-max network [21]. The presented controllers are hardware-friendly implementations based on classic fuzzy control theory, an example is shown in Figure 42.…”

1.2-mW Online Learning Mixed-Mode Intelligent Inference Engine for Low-Power Real-Time Object Recognition Processor

“…Although there are some processors which adopt the mixed architecture, historically, the mixed-mode NF processor which outperforms single domain processors has never been introduced [27], [28]. The main problems of mixed domain processors are as follows: 1) long processing delay of analog domain and digital domain operations as well as data conversion time of DAC and ADC, not satisfying the processing time requirement of the online learning operation; 2) mismatch and noise control of parallel analog circuit arrays, decreasing system performance; and 3) comparatively large power/speed/area overhead of data conversion circuits.…”

“…By adopting the energy-constrained mixed-mode system, we can drastically reduce the power consumption and increase energy efficiency while maintaining high programmability of the digital processor. Although other mixed-mode systems [27], [28] were implemented with higher complexity or better FLIPS, with consideration of different process technology they required either excessive power or area due to the overheads of the mixed-mode system.…”