A new BIST (Built-in Self-test) method for static ADC testing is proposed. The proposed method detects offset, gain, INL (Integral Non-linearity) and DNL (Differential Non-linearity) errors with a low hardware overhead. Moreover, it can solve a transient zone problem which is derived from the ADC noise in real test environments.

This paper presents a new low power BIST TPG scheme for reducing scan transitions. It uses a transition freezing and melting method which is implemented of the transition freezing block and a MUX. When random test patterns are generated from an LFSR, transitions of those patterns satisfy pseudo-random Gaussian distribution. The proposed technique freezes transitions of patterns using a freezing value. Experimental results show that the proposed BIST TPG schemes can reduce average power reduction by about 60% without performance loss and peak power by about 30% in ISCAS'89 benchmark circuits.

This paper proposes a built-in self-test (BIST) scheme for noise-tolerant testing of a digital-to-analogue converter (DAC). The proposed BIST calculates the differences in output voltages between a DAC and test modules. These differences are used as the inputs of an integrator that determines integral nonlinearity (INL). The proposed method has an advantage of random noise cancelation and achieves a higher test accuracy than do the conventional BIST methods. The simulation results show high standard noise-immunity and fault coverage for the proposed method.

A new low power test pattern generator (TPG) which can effectively reduce the average power consumption during test application is developed. The new TPG reduces the weighted switching activity (WSA) of the circuit under test (CUT) by suppressing transitions at some primary inputs which make many transitions. Moreover, the new TPG does not lose fault coverage. Experimental results on the ISCAS benchmark circuits show that average power reduction can be achieved up to 33.8% while achieving high fault coverage.

In this letter a histogram-based BIST (Built-In Self-Test) approach for deriving the main characteristic parameters of an ADC (Analog to Digital Converter) such as offset, gain and non-linearities is proposed. The BIST uses a ramp signal as an input signal and two counters as a response analyzer to calculate the derived static parameters. Experimental results show that the proposed method reduces the hardware overhead and testing time while detecting any static faults in an ADC.

Testing PLLs (phase-locked loops) is becoming an important issue that affects both time-to-market and production cost of electronic systems. Though a PLL is the most common mixed-signal building block, it is very difficult to test due to internal analog blocks and signals. In this paper, we propose a new PLL BIST (built-in self test) using the distorted frequency detector that uses only internal digital signals. The proposed BIST does not need to load any analog nodes of the PLL. Therefore, it provides an efficient defect-oriented structural test scheme, reduced area overhead, and improved test quality compared with previous approaches.

This paper proposes a new BIST (Built-In Self-Test) method for static testing of an ADC (Analog-to-Digital Converter) with transition detection method. The proposed BIST uses a triangle-wave as an input test stimulus and calculates the ADC's static parameters. Simulation results show that the proposed BIST can test both rising and falling transitions with minimal hardware overhead.