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This paper presents a new architecture for the Adaptive Neuro-Fuzzy Inference System (ANFIS) algorithm targeting FPGA implementation. This new architecture offers higher efficiency and scalability in comparison to the existing methods. The proposed architecture is modeled and simulated using VHDL and is targeted at a Xilinx FPGA. Existing implementation architectures are also modeled and comparisons...
Physical activity monitoring represents an important tool in supporting/encouraging vulnerable persons in their struggle to recover from surgery or long term illness promoting a healthy lifestyle. The paper proposes a smart, low power activity monitoring platform capable to acquire data from 4 inertial sensor modules placed on human body, temporarily store it on a mobile phone for real time data display...
The hardware implementation of an artificial neural network (ANN) using field-programmable gate arrays (FPGAs) is a research field that has attracted much interest and attention. With the developments made, the programmer is now forced to face various challenges, such as the need to master various complex hardware–software development platforms, hardware description languages, and advanced ANN knowledge...
Monitoring the human hydration level (BHL) is a key factor in preventing urinary system disorders. The paper proposes a smart holistic system that comprises two components: (1) a urine colour measurement system that can be installed in restrooms, and (2) a mobile app that can be used to interact with the measurement unit, track the user's BHL, view statistical data and advice. The main prototype was...
The PI algorithm has proven to be a popular and widely used control method, due to its relative simplicity and robustness. Despite this, the linear nature of the algorithm means it doesn't provide optimal control to non-linear systems. This paper presents a novel method of improving the performance of the PI controller using an ANFIS network to provide gain scheduling. This control scheme is applied...
The paper presents a novel neural design methodology based on the End User Programming concept. The proposed solution empowers end users, by means of abstracting the low-level hardware functionalities, to hardware implement Artificial Neural Networks (ANN) using field-programmable gate arrays (FPGA). The main outcomes include rapid ANN design and hardware implementation. A case study of an ANN as...
Urinary system disorders may be prevented by achieving a good body hydration level (BHL). This paper investigated a measurement platform set-up for detecting the shade of the (yellow) colour of urine and its integration with the IoT principles for providing ubiquitous services to the users (citizens). We propose a smart IoT-based holistic system that consists of a urine colour measurement component...
Particle swarm optimization (PSO) has proven to be a particularly popular evolutionary algorithm for the tuning of PID controllers, due to its relative simplicity and suitability as a function approximator. This paper presents a new modeling technique, featuring co-simulation between Matlab and PSIM, a specialist control and power electronics simulation environment. The tuned PID is applied to a buck...
This paper presents a 6 channels pulse width modulator with high resolution. The modulator is designed for three phase AC drives control. It is targeted for low cost FPGA implementation, and uses the special clock management units present in the FPGA. The modulator is verified first by measurements on one channel. Then it is used for open loop starting of a three phase induction motor, thus verifying...
This paper presents the hardware-software co-design platform based on FPGA developed for fast prototyping of embedded systems using hardware modules that can be easily connected and “driver” modules that can manage I/O devices and sensors basic behavior. Having this framework, adding of a new I/O peripheral needs only design and synthesis of an application specific VHDL or software module. Using neural...
This paper presents a hardware implementation of a multilayer feed-forward neural network based on back-propagation. The implementation is assumed to design and implement modules that emulate FF-BP functions with computing blocks of the predefined System Generator library and user defined blocks integrated in the System Generator library. The main application of the developed structure is an artificial...
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