Differential Nonlinearity: Ideally, any two adjacent digitalcodes correspond to output analog voltages that are exactlyone LSB apart. Differential non-linearity is a measure of theworst case deviation from the ideal 1 LSB step. For example,a DAC with a 1.5 LSB output change for a 1 LSB digital codechange exhibits 1⁄2 LSB differential non-linearity. Differentialnon-linearity may be expressed in fractional bits or as a percentageof full scale. A differential non-linearity greater than1 LSB will lead to a non-monotonic transfer function in aDAC.Gain Error (Full Scale Error): The difference between theoutput voltage (or current) with full scale input code and theideal voltage (or current) that should exist with a full scale inputcode.Gain Temperature Coefficient (Full Scale TemperatureCoefficient): Change in gain error divided by change in temperature.Usually expressed in parts per million per degreeCelsius (ppm/°C).Integral Nonlinearity (Linearity Error): Worst case deviationfrom the line between the endpoints (zero and full scale).Can be expressed as a percentage of full scale or in fractionof an LSB.LSB (Lease-Significant Bit): In a binary coded system thisis the bit that carries the smallest value or weight. Its value isthe full scale voltage (or current) divided by 2n, where n is theresolution of the converter.Monotonicity: A monotonic function has a slope whose signdoes not change. A monotonic DAC has an output thatchanges in the same direction (or remains constant) for eachincrease in the input code. the converse is true for decreasing codes.
This paper addresses a stochastic-#ow network in which each arc or node has several capacities and may
fail. Given the demand d, we try to evaluate the system reliability that the maximum #ow of the network is
not less than d. A simple algorithm is proposed "rstly to generate all lower boundary points for d, and then
the system reliability can be calculated in terms of such points. One computer example is shown to illustrate
the solution procedure.
This paper addresses a stochastic-#ow network in which each arc or node has several capacities and may
fail. Given the demand d, we try to evaluate the system reliability that the maximum #ow of the network is
not less than d. A simple algorithm is proposed "rstly to generate all lower boundary points for d, and then
the system reliability can be calculated in terms of such points. One computer example is shown to illustrate
the solution procedure.
This paper addresses a stochastic-#ow network in which each arc or node has several capacities and may
fail. Given the demand d, we try to evaluate the system reliability that the maximum #ow of the network is
not less than d. A simple algorithm is proposed "rstly to generate all lower boundary points for d, and then
the system reliability can be calculated in terms of such points. One computer example is shown to illustrate
the solution procedure.
This paper addresses a stochastic-#ow network in which each arc or node has several capacities and may
fail. Given the demand d, we try to evaluate the system reliability that the maximum #ow of the network is
not less than d. A simple algorithm is proposed "rstly to generate all lower boundary points for d, and then
the system reliability can be calculated in terms of such points. One computer example is shown to illustrate
the solution procedure.
LCD Driver datasheet
The SPF54126A, a 262144-color System-on-Chip (SoC) driver LSI designed for small and medium sizes of TFT LCD display, is capable of
supporting up to 176xRGBx220 in resolution which can be achieved by the designated RAM for graphic data. The 528-channel source
driver has true 6-bit resolution, which generates 64 Gamma-corrected values by an internal D/A converter. The source driver of
SPFD54126A adopts OP-AMP structure to enhance display quality and it cooperates with advanced circuitry techniques to reduce power
consumption.
