A Pattern Construction Scheme for Neural Network-Based Cognitive Communication

Inefficient utilization of the frequency spectrum due to conventional regulatory limitations and physical performance limiting factors, mainly the Signal to Noise Ratio (SNR), are prominent restrictions in digital wireless communication. Pattern Based Communication System (PBCS) is an adaptive and perceptual communication method based on a Cognitive Radio (CR) approach. It intends an SNR oriented cognition mechanism in the physical layer for improvement of Link Spectral Efficiency (LSE). The key to this system is construction of optimal communication signals, which consist of encoded data in different pattern forms (waveforms) depending on spectral availabilities. The signals distorted in the communication medium are recovered according to the pre-trained pattern glossary by the perceptual receiver. In this study, we have shown that it is possible to improve the bandwidth efficiency when largely uncorrelated signal patterns are chosen in order to form a glossary that represents symbols for different length data groups and the information can be recovered by the Artificial Neural Network (ANN) in the receiver site

3-D object mesh geometry compression with vector quantization

IEEE 12th Signal Processing and Communications Applications Conference -- APR 28-30, 2004 -- Kusadasi, TURKEYWOS: 000225861200076In this study, the objective is to develop a new combined method for efficient compression of classical 3-D object mesh representation. This can be realized in two primary steps: Mesh connectivity coding and data (geometry) compression. For realizing the first step, the algorithm of Isenburg [1] has been employed. For the second step, vector quantization methods have been used to compress the vertex coordinate. The difference between our study and the others is that our study uses ECVQ method for vertex coordinate compression to improve the results.IEEE, Tubitak, Istanbul Teknik Univ, Aselsan, Profile Telre, TURCom, Sgi, Datacore, Divi

Compressing mesh geometry using spectral methods and a set partitioning approach

Orcay, Özgür (Dogus Author) -- Conference full title: 14th Signal Processing and Communications Applications, IEEE 2006; Antalya; Turkey; 17 April 2006 through 19 April 2006.We propose a mesh geometry coder that utilizes spectral methods and a set partitioning approach for coding the spectral coefficients. The spectral method of [1] not only achieved high rate-distortion performance on irregular meshes, but also allowed progressive transmission of meshes by truncating the coefficient vector and performing reconstruction with a small subset of coefficients that contain most of the total energy. In this paper, mesh geometry is projected onto an orthonormal basis that is derived from the mesh topology as in [1], and the spectral coefficients are coded with the set partitioning sorting algorithm of [2]. Since the method achieves implicit bit allocation to the spectral coefficients of the three coordinates and efficiently codes the significant coefficient location information by jointly coding the zeroes in the bit planes of these coefficients the rate- distortion performance of the proposed method is superior to that of [1] as demonstrated by our experiments on common irregular meshes. The generated bit stream is also truly embedded.Spektral dönüşümle elde edilen katsayıları küme bölüntüleme yaklaşımlarıyla işleyerek 3B nesne geometrilerini kodlayan bir yöntem öneriyoruz. [1]' de anlatılan spektral yöntem düzensiz tel filelerde yüksek hız-bozunum başarımı sağlamakla kalmayıp, geriçatımı, katsayı vektörünü kırparak elde edilen ve toplam enerjisinin büyük bir bölümünü taşıyan alt vektörüyle gerçekleştirdiği için aşamalı aşamalı iletim de sağlayabilmektedir. Önerilen spektral yöntemde, nesne geometrisinin [1]'de olduğu gibi topolojiden türetilen birimdik bir taban üzerine izdüşümü alınmakta ve elde edilen katsayılar [2]'nin küme bölüntüleme algoritmasıyla kodlanmaktadır. Yöntem üç koordinata ait spektral katsayılara dolaylı bit ataması başardığı ve önemli katsayılara ait konum bilgisini bu katsayıların bit düzlemlerindeki sıfırlarını birleşik kodlayarak verimli kodlama sağladığı için, yaygın düzensiz tel fileler üzerinde yaptığımız deneylerde [1]'e göre daha iyi hız-bozunum başarımı vermektedir. Üretilen bit katarı da tamamen gönüllüdür

3-D object mesh geometry compression with vector quantization [3-B Nesne Bilgilerinin Vektör Nicemleme Yöntemleri ile Sikiştirilmasi]

IEEE;TUBITAK;Istanbul Teknik Universitesi;aselsan;Profilo Telr@Proceedings of the IEEE 12th Signal Processing and Communications Applications Conference, SIU 2004 -- 28 April 2004 through 30 April 2004 -- Kusadasi -- 64722In this study, the objective is to develop a new combined method for efficient compression of classical 3-D object mesh representation. This can be realized in two primary steps: Mesh connectivity coding and data (geometry) compression. For realizing the first step, the algorithm of Isenburg has been employed. For the second step, vector quantization methods have been used to compress the vertex coordinate. The difference between our study and the others is that our study uses ECVQ method for vertex coordinate compression to improve the results. © 2004 IEEE

3-D object mesh geometry compression with vector quantization

Bu çalışmanın amacı, bağlanırlık kodlaması için gerçeklenmiş [I]'deki algoritmayı bazı yenilikler ile uygulamak ve koordinat sıkıştırması için 3-B (3 Boyutlu) nesne gösterimleri alanında kullanımı kısıtlı olan kayıplı bir göz sıkıştırma algoritması geliştirmektir. İlk kısımda, bağlanırlık kodlamasını gerçeklemek için kullanılan algoritma ([I]) üzerinde yapılan ufak değişiklikler ile amaca uygun iyileştirmeler sağlanmıştır. İkinci kısımda ise bu alanda kullanımı kısıtlı olan Vektor Nicemleme yöntemleri gerçekleştirilmiştir. Çalışmanın diğer önerilen algoritmalardan farkı, Entropi kısıtlı Vektör Nicemleme (ECVQ) yönteminin geometri sıkıştırma algoritması olarak kullanılmasıdır. Bu sayede gerek bağlanırlık gerekse geometri sıkıştırması algoritmaları için tatmin edici hata düşürme oranlarına ulaşılmıştır.In this study, the objective is to develop a new combined method for efficient compression of classical 3-D object mesh representation. This can be realized in two primary steps: Mesh connectivity coding and data (geometry) compression. For realizing the first step, the algorithm of Isenburg [1] has been employed. For the second step, vector quantization methods have been used to compress the vertex coordinate. The difference between our study and the others is that our study uses ECVQ method for vertex coordinate compression to improve the results.Publisher's Versio

Predictive vector quantization of 3-D polygonal mesh geometry by representation of vertices in local coordinate systems

A large family of lossy 3-D mesh geometry compression schemes operate by predicting the position of each vertex from the coded neighboring vertices and encoding the prediction error vectors. In this work, we first employ entropy constrained extensions of the predictive vector quantization and asymptotically closed loop predictive vector quantization techniques that have been suggested in [3] for coding these prediction error vectors. Then we propose the representation of the prediction error vectors in a local coordinate system with an axis coinciding with the surface normal vector in order to cluster the prediction error vectors around a 2-D subspace. We adopt a least squares approach to estimate the surface normal vector from the non-coplanar, previously coded neighboring vertices. Our simulation results demonstrate that the prediction error vectors can be more efficiently vector quantized by representation in local coordinate systems than in global coordinate systems.Publisher's Versio

Compressing mesh geometry using spectral methods and a set partitioning approach [Spektral yöntemler ve küme bölüntüleme yaklaşimlariyla 3B nesne bilgilerinin sikiştirilmasi]

2006 IEEE 14th Signal Processing and Communications Applications -- 17 April 2006 through 19 April 2006 -- Antalya -- 69461Elektronik Mühendisligi Bölümü. We propose a mesh geometry coder that utilizes spectral methods and a set partitioning approach for coding the spectral coefficients. The spectral method of [1] not only achieved high rate-distortion performance on irregular meshes, but also allowed progressive transmission of meshes by truncating the coefficient vector and performing reconstruction with a small subset of coefficients that contain most of the total energy. In this paper, mesh geometry is projected onto an orthonormal basis that is derived from the mesh topology as in [1], and the spectral coefficients are coded with the set partitioning sorting algorithm of [2]. Since the method achieves implicit bit allocation to the spectral coefficients of the three coordinates and efficiently codes the significant coefficient location information by jointly coding the zeroes in the bit planes of these coefficients the rate- distortion performance of the proposed method is superior to that of [1] as demonstrated by our experiments on common irregular meshes. The generated bit stream is also truly embedded. © 2006 IEEE

Predictive vector quantization of 3-D mesh geometry by representation of vertices in local coordinate systems

In predictive 3-D mesh geometry coding, the position of each vertex is predicted from the previously coded neighboring vertices and the resultant prediction error vectors are coded. In this work, the prediction error vectors are represented in a local coordinate system in order to cluster them around a subset of a 2-D planar subspace and thereby increase block coding efficiency. Alphabet entropy constrained vector quantization (AECVQ) of Rao and Pearlman is preferred to the previously employed minimum distortion vector quatitization (MDVQ) for block coding the prediction error vectors with high coding efficiency and low implementation complexity. Estimation and compensation of the bias in the parallelogram prediction rule and partial adaptation of the AECVQ codebook to the encoded vector source by normalization using source statistics, are the other salient features of the proposed coding system. Experimental results verify the advantage of the use of the local coordinate system over the global one. The visual error of the proposed coding system is lower than the predictive coding method of Touma and Gotsman especially at low rates, and lower than the spectral coding method of Karni and Gotsman at medium-to-high rates.Publisher's Versio

Predictive vector quantization of 3-D polygonal mesh geometry by representation of vertices in local coordinate systems

Konur, Umut (Dogus Author)A large family of lossy 3-D mesh geometry compression schemes operate by predicting the position of each vertex from the coded neighboring vertices and encoding the prediction error vectors. In this work, we first employ entropy constrained extensions of the predictive vector quantization and asymptotically closed loop predictive vector quantization techniques that have been suggested in [3] for coding these prediction error vectors. Then we propose the representation of the prediction error vectors in a local coordinate system with an axis coinciding with the surface normal vector in order to cluster the prediction error vectors around a 2-D subspace. We adopt a least squares approach to estimate the surface normal vector from the non-coplanar, previously coded neighboring vertices. Our simulation results demonstrate that the prediction error vectors can be more efficiently vector quantized by representation in local coordinate systems than in global coordinate systems