Abstract

In this talk, the class of anti-uniform Huffman (AUH) codes for anti-uniform sources with finite and infinite alphabets is considered. The characteristics of such sources as well as Huffman codes for such sources are first recalled. The sequence of bits corresponding to the output of a anti-uniform source encoded with a Huffman code is modeled by a Markov source. Its characteristics are derived from the encoding procedure describing the Huffman code. The Huffman encoding process is viewed as a transmission through a channel, which input would be the input symbols, and its output, the output bits.
The class of AUH sources is known for their property of achieving minimum redundancy in several situations. It has been shown that AUH codes potentially achieve the minimum redundancy of a Huffman code of a source for which the probability of one of the symbols is known. The AUH codes are efficient in highly unbalanced cost regime, with minimal average cost among all prefix–free codes. These properties determine a wide range of applications and motivate for the study of these sources from the information theory perspective.
Starting from the AUH structure, the average codeword length, the code entropy and the average cost are derived. These results are customized for finite and infinite sources with different distributions (Poisson, negative binomial, geometric and exponential).

Bio
Daniela Tarniceriu (PhD. 1997) is a full professor at the Technical University “Gh. Asachi” of Iasi, Romania since 2001. Her research interests are in the fields of information theory, digital signal processing, statistical signal processing, data compression and encryption. She is the co-author of 8 books, 85 journal papers and 65 conference papers. She was involved in several research grants: two as scientific leader, two as coordinator, and 12 as scientist.
Since 2016, she is the Dean of the Faculty of Electronics, Telecommunications and Information Technology (ETTI) of the Technical University “Gh. Asachi” of Iasi, Romania and between 2008 and 2016 she was the head of the “Telecommunications” Department of the ETTI. Since 2013 she is the head of the Doctoral School of the ETTI.

Abstract

Recent advances in synthetic biology and chemistry are making it possible to form
networks consisting of nanoscale devices—known as nanomachines—with
applications in medicine and environmental protection. These nanoscale devices,
often known as nanomachines, have a limited ability to sense their environment,
communicate and take simple actions. A key potential application is therefore event
detection, where the nanoscale network seeks to identify the presence of an
undesirable state, such as markers of an illness.

To support event detection, the nanoscale network must be able to communicate
observations from sensing nanomachines to a fusion center, where a decision can
be made. Due to strict size and energy constraints, this communication is a
challenging problem. Recently, a new approach known as molecular communication
has been proposed, where information is encoded in the state of molecules, such as
the release time, number, or type of molecules, which diffuse from the transmitter to
the receiver through a fluid. This new medium has dramatically different features
than traditional electromagnetic and accoustic media, which requires new channel
models, as well as encoding and decoding strategies.

In this seminar, I will introduce the principles of molecular communication,
highlighting the differences from traditional communication schemes. I will then show
how molecular communication can support collaboration in nanoscale networks. In
particular, I will present a new event detection scheme for nanoscale networks,
which accounts for the unique characteristics of the underlying molecular
communication links—known as the anomalous diffusion channel.

Speaker biography

Mai Cong Trang currently is PhD candidate in Molecular Communications under the
supervision of Dr. Trung Q. Duong at Queen’s University Belfast and Dr. Malcolm
Egan at INSA Lyon. He received the B.S. degree in Electronic and Electrical
Engineering in 2008 at Le Quy Don Technical University, Vietnam. Then, in 2013, he
received the M.S. degree in Electronics and Communications Engineering at The
University of Electro‐Communications, Japan. His current research interests include
Molecular Communications, Nanomachine Networks and Bio-inspired Networks.

https://sites.google.com/view/maicongtrang/