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Rafal Tomasz Dlugosz

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Related publications (27)

Analog Programmable Distance Calculation Circuit for Winner Takes All Neural Network Realized in the CMOS Technology

Rafal Tomasz Dlugosz

This paper presents a programmable analog current-mode circuit used to calculate the distance between two vectors of currents, following two distance measures. The Euclidean (L2) distance is commonly used. However, in many situations, it can be replaced wi ...

Institute of Electrical and Electronics Engineers2016

An efficient initialization mechanism of neurons for Winner Takes All Neural Network implemented in the CMOS technology

Pierre-André Farine, Rafal Tomasz Dlugosz

The paper presents a new initialization mechanism based on a Convex Combination Method (CCM) for Kohonen self-organizing Neural Networks (NNs) realized in the CMOS technology. A proper selection of initial values of the neuron weights exhibits a strong imp ...

Elsevier Science Inc2015

A low power, low chip area decimation filter for Σ - Δ modulator for flywheel MEMS gyro realized in the CMOS 180 nm technology

Steve Tanner, Pierre-André Farine, Rafal Tomasz Dlugosz, Patrick Stadelmann

The paper presents a low power and low chip area decimation filter for a 15-bits Σ-Δ analog-to-digital converter (ADC) designed for a flywheel MEMS gyroscope. In contrary to typical solutions, in which decimation is performed after each filtering stage, in ...

IEEE2012

A programmable triangular neighborhood function for a Kohonen self-organizing map implemented on chip

Rafal Tomasz Dlugosz

An efficient transistor level implementation of a flexible, programmable Triangular Function (TF) that can be used as a Triangular Neighborhood Function (TNF) in ultra-low power, self-organizing maps (SOMs) realized as Application-Specific Integrated Circu ...

2012

Convex combination initialization method for kohonen neural network implemented in the CMOS technology

Pierre-André Farine, Rafal Tomasz Dlugosz

The paper presents a new CMOS implementation of the initialization mechanism for Kohonen self-organizing neural networks. A proper selection of initial values of the weights of the neurons exhibits a significant impact on the quality of the learning proces ...

2012

Power efficient asynchronous multiplexer for X-ray sensors in medical imaging analog front-end electronics

Pierre-André Farine, Rafal Tomasz Dlugosz

This paper presents a new power efficient asynchronous multiplexer(MUX) for application in analog front-endelectronics(AFE) used in X-ray medical imaging systems. Contrary to typica lsynchronous MUXes that have to be controlled by a clock, this circuit fea ...

Elsevier2011

Parallel Programmable Asynchronous Neighborhood Mechanism for Kohonen SOM Implemented in CMOS Technology

Rafal Tomasz Dlugosz

We present a new programmable neighborhood mechanism for hardware implemented Kohonen self-organizing maps (SOMs) with three different map topologies realized on a single chip. The proposed circuit comes as a fully parallel and asynchronous architecture. T ...

Institute of Electrical and Electronics Engineers2011

Current-Mode Analog Adaptive Mechanism for Ultralow-Power Neural Networks

Rafal Tomasz Dlugosz

Neural networks (NNs) implemented at the transistor level are powerful adaptive systems. They can perform hundreds of operations in parallel but at the expense of a large number of building blocks. In the case of analog realization, an extremely low chip a ...

Institute of Electrical and Electronics Engineers2011

Power Efficient Hardware Implementation of a Fuzzy Neural Network

Rafal Tomasz Dlugosz

This paper presents a digital, transistor level implemented neo-fuzzy neural network. This type of neural network is particularly well suited for real-time applications like those encountered in signal processing and nonlinear system identification. We con ...

Technical University of Lodz2010

Programmable Triangular Neighborhood Functions of Kohonen Self-Organizing Maps Realized in CMOS Technology

Rafal Tomasz Dlugosz

The paper presents a programmable triangular neighborhood function for application in low power transistor level implemented Kohonen self-organized maps (SOMs). Detailed simulations carried out for the software model of such network show that the triangula ...

2010

A power-efficient, current-mode, binary-tree min / max circuit for Kohonen self-organizing feature maps and nonlinear filters

Rafal Tomasz Dlugosz

A novel current-mode, binary-tree Min / Max circuit for application in analog neural networks and filters has been presented. In the proposed circuit input currents are first converted to step signals with equal amplitudes and different delays that are pro ...

2010

Programmable Triangular Neighborhood Function for Kohonen Self-Organizing Map Implemented on Chip

Rafal Tomasz Dlugosz

A new hardware implementation of the triangular neighborhood function (TF) for ultra-low power, self-organizing maps (SOM) is presented. Simulations carried out in the software model of this network show that even for low signal resolutions (3-6 bits) perf ...

Technical University of Lodz2010

A Flexible, Low-Power, Programmable Unsupervised Neural Network Based on Microcontrollers for Medical Applications

Rafal Tomasz Dlugosz

We present an implementation and laboratory tests of a winner takes all (WTA) artificial neural network (NN) on two microcontrollers (μC) with the ARM Cortex M3 and the AVR cores. The prospective application of this device is in wireless body sensor networ ...

School of Engineering, The University of Waikato2010

Kohonen Winner Takes All Neural Network Realized on Microcontrollers with AVR and ARM Cores

Rafal Tomasz Dlugosz

This paper presents realization and the laboratory tests of the Kohonen winner takes all (WTA) neural network (NN) realized on microcontrollers (μC) with the AVR and ARM CortexM3 cores. Both μCs have been placed on a single testing board especially designe ...

Technical University of Lodz2010

Operational Amplifier for Switched-Capacitors Systems Realized in Different CMOS Technologies

Rafal Tomasz Dlugosz

2010

Low power current-mode binary-tree asynchronous Min/Max circuit

Rafal Tomasz Dlugosz

A novel, current-mode, binary-tree, asynchronous Min/Max circuit for application in nonlinear filters as well as in analog artificial neural networks is proposed. The relatively high precision above 99% can be achieved by eliminating the copying of the inp ...

2010

Realization of the Conscience Mechanism in CMOS Implementation of Winner-Takes-All Self-Organizing Neural Networks

Rafal Tomasz Dlugosz

This paper presents a complementary metal–oxide– semiconductor (CMOS) implementation of a conscience mechanism used to improve the effectiveness of learning in the winnertakes- all (WTA) artificial neural networks (ANNs) realized at the transistor level. T ...

Institute of Electrical and Electronics Engineers2010

Lukasiewicz fuzzy logic networks and their ultra low power hardware implementation

Rafal Tomasz Dlugosz

In this paper, we propose a new category of current-mode Łukasiewicz OR and AND logic neurons and ensuing logic networks along with their ultra-low power realization. The introduced circuits can operate in a wide range of the input signals varying in-betwe ...

Elsevier2010

An influence of current-leakage in analog memory on training Kohonen neural network implemented on silicon

Rafal Tomasz Dlugosz

The paper presents how the current leakage encountered in capacitive analog memories affects the learning process of hardware implemented Kohonen neural networks (KNN). MOS transistor leakage currents, which strongly depend on temperature, increase the net ...

2010

New Fast Training Algorithm Suitable For Hardware Kohonen Neural Networks Designed For Analysis Of Biomedical Signals

Rafal Tomasz Dlugosz

A new optimized algorithm for the learning process suitable for hardware implemented Winner Takes Most Kohonen Neural Network (KNN) has been proposed in the paper. In networks of this type a neighborhood mechanism is used to improve the convergence propert ...

Insticc-Inst Syst Technologies Information Control & Communication, Avenida D Manuel L, 27A 2 Esquerdo, Setubal, 2910-595, Portugal2009

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