BitCoin transactions are malleable in a sense that given a transaction an adversary can easily construct an equivalent transaction which has a different hash. This can pose a serious problem in some BitCoin distributed contracts in which changing a transaction’s hash may result in the protocol disruption and a financial loss. The problem mostly concerns protocols, which use a ”refund” transacti...

A simple linear neuron model with constrained Hebbian-type synaptic modification is analyzed and a new class of unconstrained learning rules is derived. It is shown that the model neuron tends to extract the principal component from a stationary input vector sequence.

We consider m independent exponential servers in parallel, driven by the same deterministic input. This is a modification of the Flatto-Hahn-Wright model which turns out to be easily tractable. We focus on the time-stationary distribution of the number of customers which is obtained using the Palm inversion formula.

For binary neural networks (BNNs), constructive covering frameworks have been investigated recently. While these frameworks are fast, they have limitations of generalization and accurate classification for learning from limited number of samples. In this paper, we propose modified constructive-covering algorithm (MCCA), which consists of two processes: generalization process and modification pr...

BACKGROUND Cycles of covalent modification are ubiquitous motifs in cellular signalling. Although such signalling cycles are implemented via a highly concise set of chemical reactions, they have been shown to be capable of producing multiple distinct input-output mapping behaviours - ultrasensitive, hyperbolic, signal-transducing and threshold-hyperbolic. RESULTS In this paper, we show how th...

The C-value/NC-value algorithm, a hybrid approach to automatic term recognition, has been originally developed to extract multiword term candidates from specialised documents written in English. Here, we present three main modifications to this algorithm that affect how the obtained output is refined. The first modification aims to maximise the number of real terms in the list of candidates wit...

Human and animal studies show that mammalian brains undergo massive synaptic pruning during childhood, losing about half of the synapses by puberty. We have previously shown that maintaining the network performance while synapses are deleted requires that synapses be properly modified and pruned, with the weaker synapses removed. We now show that neuronal regulation, a mechanism recently observ...

The Enterprise Resource Planning (ERP) system is a breed of configurable package systems that aims to disseminate transactional information of the entire organization to users in a timely and efficient fashion under a uniform system environment. However, ERP systems often fail to live up their claim to improve operational efficiency and strategic effectiveness due to misfits between the standar...

Parallels between the signal processing tasks and biological neurons lead to an understanding of principles self-organized optimization input recognition. In present paper, we discuss such similarities among technical systems. We propose adding well-known STDP synaptic plasticity rule direct weight modification towards state associated with maximal difference background noise correlated signals...