Supervised Adaptive Hamming Net for Classification of Multiple-Valued Patterns

1997 ◽  
Vol 08 (02) ◽  
pp. 181-200
Author(s):  
Cheng-An Hung ◽  
Sheng-Fuu Lin
Keyword(s):  
Upper Bound ◽  
Incremental Learning ◽  
Arbitrary Sequence ◽  
Input Output ◽  
Multiple Valued Logic

A Supervised Adaptive Hamming Net (SAHN) is introduced for incremental learning of recognition categories in response to arbitrary sequence of multiple-valued or binary-valued input patterns. The binary-valued SAHN derived from the Adaptive Hamming Net (AHN) is functionally equivalent to a simplified ARTMAP, which is specifically designed to establish many-to-one mappings. The generalization to learning multiple-valued input patterns is achieved by incorporating multiple-valued logic into the AHN. In this paper, we examine some useful properties of learning in a P-valued SAHN. In particular, an upper bound is derived on the number of epochs required by the P-valued SAHN to learn a list of input-output pairs that is repeatedly presented to the architecture. Furthermore, we connect the P-valued SAHN with the binary-valued SAHN via the thermometer code.

scholarly journals Incremental Learning for Classification of Unstructured Data Using Extreme Learning Machine

Algorithms ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 158 ◽  
Author(s):  
Sathya Madhusudhanan ◽  
Suresh Jaganathan ◽  
Jayashree L S
Keyword(s):  
Extreme Learning Machine ◽  
Incremental Learning ◽  
Streaming Data ◽  
Unstructured Data ◽  
Feed Forward Neural Network ◽  
Training Time ◽  
Class Labels ◽  
Learning Machine ◽  
Over Time

Unstructured data are irregular information with no predefined data model. Streaming data which constantly arrives over time is unstructured, and classifying these data is a tedious task as they lack class labels and get accumulated over time. As the data keeps growing, it becomes difficult to train and create a model from scratch each time. Incremental learning, a self-adaptive algorithm uses the previously learned model information, then learns and accommodates new information from the newly arrived data providing a new model, which avoids the retraining. The incrementally learned knowledge helps to classify the unstructured data. In this paper, we propose a framework CUIL (Classification of Unstructured data using Incremental Learning) which clusters the metadata, assigns a label for each cluster and then creates a model using Extreme Learning Machine (ELM), a feed-forward neural network, incrementally for each batch of data arrived. The proposed framework trains the batches separately, reducing the memory resources, training time significantly and is tested with metadata created for the standard image datasets like MNIST, STL-10, CIFAR-10, Caltech101, and Caltech256. Based on the tabulated results, our proposed work proves to show greater accuracy and efficiency.

scholarly journals DENSE CODING WITH MULTIPARTITE QUANTUM STATES

2006 ◽  
Vol 04 (03) ◽  
pp. 415-428 ◽  
Author(s):  
DAGMAR BRUß ◽  
MACIEJ LEWENSTEIN ◽  
ADITI SEN(DE) ◽  
UJJWAL SEN ◽  
GIACOMO MAURO D'ARIANO ◽  
...  
Keyword(s):  
Quantum State ◽  
Upper Bound ◽  
Arbitrary Number ◽  
Information Transfer ◽  
Quantum States ◽  
Dense Coding ◽  
Joint Operations ◽  
Single Receiver

We consider generalizations of the dense coding protocol with an arbitrary number of senders and either one or two receivers, sharing a multiparty quantum state, and using a noiseless channel. For the case of a single receiver, the capacity of such information transfer is found exactly. It is shown that the capacity is not enhanced by allowing the senders to perform joint operations. We provide a nontrivial upper bound on the capacity in the case of two receivers. We also give a classification of the set of all multiparty states in terms of their usefulness for dense coding. We provide examples for each of these classes, and discuss some of their properties.

scholarly journals Analisis sektor unggulan perekonomian Indonesia: Model input-output

SOROT ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. 119
Author(s):  
Armelly Armelly ◽  
Muhammad Rusdi ◽  
Esti Pasaribu
Keyword(s):  
Agricultural Sector ◽  
Analysis Data ◽  
Input Output ◽  
Microsoft Excel ◽  
Processing Industry ◽  
Output Table ◽  
Industry Sector ◽  
Forward Linkage ◽  
Backward Linkages

Penelitian ini bertujuan untuk mengetahui peranan  sektor  ekonomi termasuk  bagaimana  keterkaitan masing-masing  sektor tersebut mempengaruhi  ekonomi di Indonesia. Penelitian ini menggunakan  data Tabel Input-Output Indonesia  menurut  Harga Dasar Klasifikasi 17  Sektor yang  diagregasi  menjadi 9  sektor. Metode  analisis  dilakukan  menggunakan input-output  model  yang  penghitungannya dibantu  dengan menggunakan  program Microsoft Excel. Dari penelitian, didapatkan bahwa sektor  industri  pengolahan memperlihatkan keterkaitan langsung kedepan dengan nilai tertinggi. Hal ini dapat ditafsirkan bahwa pertumbuhan ekonomi Indonesia  lebih  banyak dipengaruhi  oleh pertumbuhan sektor  industri  pengolahan dan memberikan makna bahwa basis perekonomian Indonesia saat ini bertumpu pada sektor industri pengolahan. Lebih jauh lagi, sektor  industri  pengolahan memiliki hubungan besar dengan sektor pertanian dimana sektor ini merupakan penyumbang input antara terbesar bagi sektor pertanian. Dengan demikian, kemajuan pada sektor industri pengolahan akan serta merta memajukan sektor pertanian sebagai multiplier efeknya.This study aims to  analyze  the magnitude of the forward  and  backward linkages  of the any sector with others. The data used in this study were data from Indonesia Input-Output Table Domestic Transaction on the Basic Prices Classification of 17 sectors aggregated into 9 sectors obtained from Central Bureau of Statistics Republic of Indonesia (BPS). The method of analysis data was using the input-output model whose calculations assisted by Microsoft Excel program. The results showed that processing industry sector was a greatest total forward linkage. For that, we can say that economics growth in Indonesia still having processing industry as a leading sector. Further, this sector was having a big relationship with agricultural sector which contributed as a bigest input for agriculture. In conclusion, any development in processing industri sector will be develop agricultural sector as multiplyer effect.

scholarly journals On the Number of Similar Instances of a Pattern in a Finite Set

10.37236/4972 ◽  
2016 ◽  
Vol 23 (4) ◽  
Author(s):  
Bernardo M. Ábrego ◽  
Silvia Fernández-Merchant ◽  
Daniel J. Katz ◽  
Levon Kolesnikov
Keyword(s):  
Arithmetic Progression ◽  
Finite Subset ◽  
Upper Bound ◽  
Point Subset ◽  
Finite Set ◽  
Equilateral Triangles ◽  
Optimal Configurations ◽  
Full Classification ◽  
General Method

New bounds on the number of similar or directly similar copies of a pattern within a finite subset of the line or the plane are proved. The number of equilateral triangles whose vertices all lie within an $n$-point subset of the plane is shown to be no more than $\lfloor{(4 n-1)(n-1)/18}\rfloor$. The number of $k$-term arithmetic progressions that lie within an $n$-point subset of the line is shown to be at most $(n-r)(n+r-k+1)/(2 k-2)$, where $r$ is the remainder when $n$ is divided by $k-1$. This upper bound is achieved when the $n$ points themselves form an arithmetic progression, but for some values of $k$ and $n$, it can also be achieved for other configurations of the $n$ points, and a full classification of such optimal configurations is given. These results are achieved using a new general method based on ordering relations.

Kinematic Structure Analysis and Classification of Single-Loop Spatial Linkage Mechanisms

1992 ◽  
Author(s):  
Y. B. Zhou ◽  
R. G. Fenton
Keyword(s):  
Kinematic Structure ◽  
Classification Criterion ◽  
Input Output ◽  
Linkage Mechanism ◽  
Symbolic System ◽  
Maximum Order ◽  
Single Loop ◽  
Output Displacement ◽  
Displacement Equation

Abstract This paper covers the following areas: all practical and typical kinematic input pairs used in a single-loop spatial linkage mechanism (SSLM) are classified using a new symbolic system; four basic groups of SSLMs are defined; and a new kinematic structure classification criterion is proposed, which provides a method to determine the maximum finite number of closures for the mechanism and the maximum order of the input-output displacement equation, free of extraneous roots, describing the kinematics of the SSLMs.

Discontinuities in Criminal Law

2021 ◽  
Vol 22 (1) ◽  
pp. 137-157
Author(s):  
Avlana K. Eisenberg
Keyword(s):  
Criminal Law ◽  
Drastic Change ◽  
Fine Tuning ◽  
Input Output ◽  
Theories Of Punishment ◽  
The Law ◽  
Inputs And Outputs

Abstract The law values fairness, proportionality, and predictability. Accordingly, in the context of criminal law, punishments should be carefully calibrated to reflect the harm caused by an offense and the culpability of the offender. Yet, while this would suggest the dominance of “smooth” input/output relationships—for example, such that a minuscule increase in culpability would result in a correspondingly small increase in punishment—in fact, the law is laden with “bumpy” input/output relationships. Indeed, a minuscule change in input (be it of harm, culpability, or any number of other measures) may result in a drastic change in output, creating significant discontinuities. Leading scholars have argued that smooth input/output relationships, which feature careful gradation and calibration, better accord with dominant theories of punishment than do bumpy relationships, which lack fine-tuning. Accepting as a starting premise that smooth input/ output relationships are to be preferred in the criminal law, this Article focuses on the significant doctrinal and practical impediments to smoothing out these relationships. This analysis reveals challenges to smoothing out relationships between inputs and outputs, as well as the difficulties associated with addressing discontinuous relationships among inputs and outputs. Specifically, it exposes the law’s classification of inputs and outputs itself as contestable and responsible for a range of hard-to-resolve discontinuities. In doing so, this Article begins the task of laying the groundwork for further analysis and possible reforms.

Link-Centre and Indexes of a Kinematic Chain

1992 ◽  
Author(s):  
V. P. Agrawal ◽  
J. N. Yadav ◽  
C. R. Pratap
Keyword(s):  
Kinematic Chain ◽  
Degree Of Freedom ◽  
Input Output ◽  
Function Generator ◽  
Kinematic Chains ◽  
Graph Theoretic ◽  
Optimum Selection ◽  
Theoretic Concept ◽  
Selection Of

Abstract A new graph theoretic concept of link-centre of a kinematic chain is introduced. The link-centre of a kinematic chain is defined as a subset of set of links of the kinematic chain using a hierarchy of criteria based on distance concept. A number of structural invariants are defined for a kinematic chain which may be used for identification and classification of kinematic chains and mechanisms. An algorithm is developed on the basis of the concept of distance and the link-centre for optimum selection of input, output and fixed links in a multi-degree-of-freedom function generator.

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