15 papers · ranked by Valyu relevance
Jesús E. Garca, Verónica A. González-López, Gustavo H. Tasca, Karina Y. Yaginuma + 1 more
In the framework of coding theory, under the assumption of a Markov process $(X_{t})$ on a finite alphabet $A,$ the compressed representation of the data will be composed of a description of the model used to code the data and the encoded data. Given the model, the Huffman’s algorithm is optimal for the number of bits…
Byron H. Price, Jeffrey P. Gavornik
While it is universally accepted that the brain makes predictions, there is little agreement about how this is accomplished and under which conditions. Accurate prediction requires neural circuits to learn and store spatiotemporal patterns observed in the natural environment, but it is not obvious how such information…
James V. Stone
Shannon's mathematical theory of communication defines fundamental limits on how much information can be transmitted between the different components of any man-made or biological system. This paper is an informal but rigorous introduction to the main ideas implicit in Shannon's theory. An annotated reading list is…
Amir Said
Entropy coding, compression, complexity This introduction to arithmetic coding is divided in two parts. The first explains how and why arithmetic coding works. We start presenting it in very general terms, so that its simplicity is not lost under layers of implementation details. Next, we show some of its basic…
Aida Koch, Alix Petit
In this article, we will analyze in detail the coding limit of an individual sequence by introducing the latest developments brought by the Set Shaping Theory. This new theory made us realize that there is a huge difference between source entropy and zero order empirical entropy. Understanding the differences between…
Nithin Nagaraj, Arun Somani
Error detection is a fundamental need in most computer networks and communication systems in order to combat the effect of noise. Error detection techniques have also been incorporated with lossless data compression algorithms for transmission across communication networks. In this paper, we propose to incorporate a…
Niklas Larsson
Text compression schemes and compact data structures usually combine sophisticated probability models with basic coding methods whose average codeword length closely match the entropy of known distributions. In the frequent case where basic coding represents runlengths of outcomes that have probability p, i.e. the…
Christian Schmidt, Adrian Vdberg, Alix Petit
One of the biggest criticisms of the Set Shaping Theory is the lack of a practical application. This is due to the difficulty of its application. In fact, to apply this technique from an experimental point of view we must use a table that defines the correspondences between two sets. However, this approach is not…
Rahul Bhui, Samuel J. Gershman
The theory of decision by sampling (DbS) proposes that an attribute’s subjective value is its rank within a sample of attribute values retrieved from memory. This can account for instances of context dependence beyond the reach of classic theories which assume stable preferences. In this paper, we provide a normative…
Lei M. Li, Boris Ryabko
We consider the lossless compression bound of any individual data sequence. Conceptually, its Kolmogorov complexity is such a bound yet uncomputable. According to Shannon’s source coding theorem, the average compression bound is $nH$, where n is the number of words and H is the entropy of an oracle probability…
Valéria G. Pedrosa, Max H. M. Costa, Sangun Park
The index coding problem consists of a system with a server and multiple receivers with different side information and demand sets, connected by a noiseless broadcast channel. The server knows the side information available to the receivers. The objective is to design an encoding scheme that enables all receivers to…
Romain Brette
“Neural coding” is a popular metaphor in neuroscience, where objective properties of the world are communicated to the brain in the form of spikes. Here I argue that this metaphor is often inappropriate and misleading. First, when neurons are said to encode experimental parameters, the implied communication channel…
Jia Lu, Ryan Tsoi, Nan Luo, Yuanchi Ha + 8 more
Dynamical systems often generate distinct outputs according to different initial conditions, and one can infer the corresponding input configuration given an output. This property captures the essence of information encoding and decoding. Here, we demonstrate the use of self-organized patterns, combined with machine…
Rodrick Wallace
The living state is cognitive at every scale and level of organization. Since it is possible to associate a broad class of cognitive processes with ‘dual’ information sources, many pathologies can be addressed using statistical models based on the Shannon Coding, the Shannon-McMillan Source Coding, the Rate Distortion…
Miloje Rakočević
In some previous works (2018a,b; 2019, 2021a,b, 2022) we presented a new type of mirror symmetry, expressed in the set of protein amino acids; such a symmetry, that it simultaneously represents the semiotic essence of the genetic code. In this paper we provide new evidences that the genetic code represents the unity of…