Abstract
An account is given on the joint time-frequency analysis (JTFA) and the short time-frequency transform algorithm in particular as an alternative technique for dynamic testing of analog to digital converters (ADCs). It is shown that this technique can lead to a significant improvement in ADC testing mainly due the possibility of using non-stationary signals allowing a more rapid test capable of analyzing even localized features.

Abstract
Analog-to-digital converter (ADC) characterization is usually performed using stationary stimuli like sine waves. However, the use of a non-stationary stimulus, besides providing testing conditions closer to those found in real applications, can lead to interesting improvements in ADC testing speed, This kind of signal needs proper processing techniques in order to extract useful information. In this paper we propose the use of joint time-frequency analysis (JTFA) for this purpose. The basic principles of the technique, and how it can be used in ADC testing are presented. in particular, a method for characterising an ADC on its entire bandwidth using a single stimulus is described.

Abstract
The estimation of the harmonic content of an ADC output is fundamental to evaluate its suitability to perform according the requirements specified for an application. The use of the traditional frequency analysis leads to a large hardware overhead due to the amount of on-chip processing being involved, or to a large quantity of data to be transferred in case the processing is performed in a tester. This paper presents an algorithm capable of estimating the harmonics with similar accuracy but with the advantage of being more suitable for a BIST implementation, since it requires a reduced number of on-chip operations, and that only a small set of values has to be supplied outside the chip for further processing. It relies, on the fact that harmonics generated by an ADC are mathematical related with the polynomial coefficients of its transfer function. ADC offset and gain errors can also be measured.

Abstract
A procedure is proposed to estimate an analogue-to-digital converter's signal-to-noise plus distortion ratio using the histogram method. The procedure provides results that are in close agreement with the ones obtained with the spectral analysis and sinewave fitting methods. It is shown that the errors obtained by using former implementations of the histogram method are due to not considering the input stimulus probability density function, and it is shown how these errors can be rectified.

Abstract
As digital design methodologies and tools are evolving to higher abstraction levels, teaching the low-level concepts of digital electronic system design is becoming increasingly challenging. The raise of the design abstraction level and, more recently, the ability of AI-assisted automated design is pushing the interest of students away from the lower-level details of the digital world. Nevertheless, digital electronic systems are (still) made of transistors, gates and flip-flops, and people do need to keep this basic knowledge to be able to build efficient circuits, understand them and develop the essential electronic design automation tools. For learning these subjects, hands-on experimentation, and learning by doing, is proven to be an effective tool, and when students finally see and feel the results of their designs, motivation raises rapidly. This paper presents the technical aspects of a platform created in the DECEL project to support an FPGA-based remote laboratory based on a commercial single-board computer that can be located somewhere in the Internet. This computer runs a Linux operating system and is based on an AMD/XILINX device that integrates in the same chip an ARM Cortex A9 CPU and a region of FPGA programmable logic. The user develops a digital circuit using standard hardware-description languages (Verilog or VHDL) and runs the implementation tools for the target FPGA using a very simple web interface running in a remote server.

Abstract
This demo shows an infrastructure that allows for easy implementation of real remote labs. In this infrastructure, several nodes are remotely interconnected by publishing/subscribing MQTT messages. There are physical nodes capable of connecting to real circuits and/or sensors/actuators, and virtual nodes that implement simulated versions of circuits that interact remotely with signals from other nodes. The latencies that occur are low enough for groups of students located in different physical locations to benefit from a near real-time experience in interacting with the circuits thus implemented.