Correction to "Linear and Logarithmic Capacities in Associative Neural Networks"

نویسندگان

  • Santosh S. Venkatesh
  • Demetri Psaltis
چکیده

J. Ma, J. Wu, and Q. Cheng kindly pointed out that [1, Proof of Proposition 1(b)] contains an overcount. The statement of the proposition reads: Let n be the family of bases for with all basis elements constrained to be binary n-tuples; (i.e., E = fe1; e2; . . . ; eng 2 n if, and only if, e1, e2; . . . ; en 2 f 1;+1g are linearly independent [over the field of the reals]). Then, asymptotically as n ! 1, almost all vectors u 2 f 1;+1g have a representation of the form

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Self-Reconstructing Algorithm for Single and Multiple-Sensor Fault Isolation Based on Auto-Associative Neural Networks

Recently different approaches have been developed in the field of sensor fault diagnostics based on Auto-Associative Neural Network (AANN). In this paper we present a novel algorithm called Self reconstructing Auto-Associative Neural Network (S-AANN) which is able to detect and isolate single faulty sensor via reconstruction. We have also extended the algorithm to be applicable in multiple faul...

متن کامل

Linear and Logarithmic Capacities in Associative Neural Networks

A model of associative memory incorporating global linearity and pointwise nonlinearities in a state space of n-dimensional binary vectors is considered. Attention is focused on the ability to store a prescribed set of state vectors as attractors within the model. Within the framework of such associative nets, a specific strategy for information storage that utilizes the spectrum of a linear op...

متن کامل

Linear and logarithmic capacities in associative neural networks

A model of associative memory incorporating global linearity and pointwise nonlinearities in a state space of n-dimensional binary vectors is considered. Attention is focused on the ability to store a prescribed set of state vectors as attractors within the model. Within the framework of such associative nets, a specific strategy for information storage that utilizes the spectrum of a linear op...

متن کامل

Predicting the buckling Capacity of Steel Cylindrical Shells with Rectangular Stringers under Axial Loading by using Artificial Neural Networks

A parametric study was carried out in order to investigate the buckling capacity of the vertically stiffened cylindrical shells. To this end ANSYS software was used. Cylindrical steel shells with different yield stresses, diameter-to-thickness ratios (D/t) and number of stiffeners were modeled and their buckling capacities were calculated by displacement control nonlinear static analysis.  Radi...

متن کامل

Cellular Optimal Linear Associative Memories for Statistical Process Control: A Preliminary Study and Proposal

The continuous detection and correction of unnatural process behaviours, due to special causes of variations, is a basic task in manufacturing to maintain any process stable and predictable. For this purpose, updated tools for Statistical Process Control have been studied so far, like the use of Artificial Neural Networks for pattern recognition in control charts. In this paper a preliminary st...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • IEEE Trans. Information Theory

دوره 53  شماره 

صفحات  -

تاریخ انتشار 2007