Preserving Privacy of Finite Impulse Response Systems

Privacy Preserving Reputation Systems

Reputation systems provide mechanisms for multiple parties, in a community, to quantify the trust between one another and to encourage adherence to contract in e-commerce. In this thesis we provide two protocols to calculate the reputation value of participant agents in peer to peer community, using a private, additive and fully decentralized manner. The first protocol considers the churn rate ...

Privacy-Preserving Database Systems

Privacy is today an important concern for both users and enterprises. Therefore, intense research is today being carried out on various aspects of privacy-preserving data management systems. In this paper, we focus on database management systems (DBMS) able to enforce privacy promises encoded in privacy languages such as P3P. In particular, in the paper, we first present an overview of the P3P ...

Interpolated Finite Impulse Response (IFIR)

The finite impulse response filters are inherently stable and have linear phase response property. The main drawback of these filters is lies in requirement of higher orders for similar magnitude response compared to Infinite Impulse response filters. Also the amount of computational complexity needed for the implementation of the filter, especially for the filters with narrow transition band i...

Finite Impulse Response Neural Networks

A neural network architecture, which models synapses as Finite Impulse Response (FIR) linear lters, is discussed for use in time series prediction. Analysis and methodology are detailed in the context of the Santa Fe Institute Time Series Prediction Competition. Results of the competition show that the FIR network performed remarkably well on a chaotic laser intensity time series.

Finite Impulse Response ( FIR ) Filters