The Pros And Cons Of Neuro-Organial Intelligence

We have seen that the essence or origin of all that exists is intelligence, and it is organized in similar patterns throughout the Universe. Therefore, we called it Universal Intelligence. By inference, we understand that this principle is not foreign or external to the universe, but that it is rather intrinsic, innate in all its manifestations, all phenomena of Life. Let's see what the definitions of the word 'innate' tells us: 'that which exists inside'; 'that which is with'; 'native or natural'; 'that which is essential in nature'. And the meaning of essential: 'what is in itself'; 'own and permanent identity'. The essential nature of everything that exists, all beings, animated or inanimated, including Man, is therefore the Universal Intelligence, and we say that this is innate and gives them an identical essence that unites them despite their apparent or superficial difference.

Whether there is more behind human behavior than can be explained solely by neural phenomena has been the subject of much time-worn scientific and philosophical debate. In regards to this question, two primary classes of alternative explanations come to mind: the human soul and the environment. The former of these involves a possible internal, individualistic force guiding behavior beyond the guides provided by the brain; many feel that the topic of the human soul is best left in the realm of the philosophical. Environmental influences on behavior, however, are quite pertinent to scientific investigations into the brain/behavior dichotomy. Whether and to what extent

Introduction 802.11AC basics Why 802.11ac? 802.11ac technology overview Backward compatibility RF spectrum Multistation MAC throughput > 1 Gbps 256 QAM Wider channels More spatial streams Downlink multi-user MIMO Pros of 802.11ac Cons of 802.11ac Strategy and planning for 802.11ac migration Site planning basics Planning process Minimum requirements and actions to implement 802.11ac Aruba recommendations for 802.11ac migration General Capacity RF planning Installation Wireless RF coverage considerations and questionnaire Summary 3 3 3 4 4 4 5 5 5 5 6 6 6 6 6 6 7 8 8 8 8 8 9 10

Between the input and the output, the preceding figure shows a black box that can contain any number of things: fuzzy systems, linear systems, expert systems, neural networks, differential equations, interpolated multi dimensional lookup tables, or even a spiritual advisor, just to name a few of the possible options. Clearly the list could go on and on.Of the dozens of ways to make the black box work, it turns out that fuzzy is often the very best way. As Lotfi Zadeh, who is considered to be the father of fuzzy logic, once remarked: "In almost every case you can build the same product without fuzzy logic, but fuzzy is faster and

Fuzzy logic is an attractive technique particularly in cases where target problems are difficult to model with traditional mathematical models, but are easier to understand by human at the same time With the characteristic of future cognitive radio in mind, the capability of fuzzy logic offer good potential to be applied. Instead of using complicated mathematical formulations, fuzzy logic uses human-understandable fuzzy sets and inference rules (e.g. IF, THEN, ELSE, AND, OR, NOT) to obtain the solution that satisfies the desired system objectives. The main advantage of fuzzy logic is its low complexity. Therefore, fuzzy logic is suitable for real-time cognitive radio applications in which the response time is critical to system performance. A fuzzy logic control system can be used to obtain the solution to a problem given imprecise, noisy, and incomplete input information. In general, there are three major components in a fuzzy logic control system: fuzzifier, fuzzy logic processor, and defuzzifier (Figure 4.4). While the fuzzifier is used to map the crisp inputs into fuzzy sets, the fuzzy logic processor implements an inference engine to obtain the solution based on predefined sets of rules. Then, the defuzzifier is applied to transform the solution to the crisp output. Fuzzy logic is often used in decision making to select the best suited SU for spectrum access at a given time. This technique when combined with neural networks is used in CR networks, multihop routing or for detecting unauthorized

The human brain is composed of many important parts of everyday life. The exterior part of the brain has 9 part in which include are divided into different sections, lobes, cortex, and areas. Within the lobes, it includes frontal, parietal, occipital, and temporal lobes. In cortexes, it has the motor cortex, and the sensory cortex. Within the areas section it includes Broca’s Area. The cerebellum is a small version of the brain, and the cerebrum is the like the whole brain. Although the brain is about three pounds blood flows through the brain about 750-1,000 milliliters (mL) per minute, (Disabled World, 2008) (Brain Trivia, (n.d.)).

We can conclude that the reuse of existing sites have a large impact also when a denser MaBS is deployed in order to compensate for wall attenuation. However, the situation is different for the deployment of new sites, unless the carrier aggregation functionality of LTA-A RAT is used. So we can summarize that, the main lack of the next generation network is recognized as limited coverage with small cell solutions like femtocells, picocells deployed with 5G mmW system and Wi-Fi. In another hand, we have the lack of the capacity limited by the macro sites. The solution to these two problems, is to investigate the cooperative layouts of macro sites with femtocells, 5G mmW PBS or Wi-Fi to achieve the trade-offs and the synergies between cost, capacity and coverage.

Artificial neural network was combined with the genetic algorithm to get the more optimized prediction . An improved technique that uses artificial neural network with photovoltaic system was proposed by Isa et al.that utilizes perceptron model with Levenberg Marquardt algorithm. Apart from neural network Fuzzy logic has also been being used in weather prediction models. The rainfall was classified into three fuzzy sets which can be predicted by making use of simple fuzzy rules . Also a fuzzy self-regression model was proposed by Lu Feng and Xu xiao Guang which makes use of the form of self-related sequence number according to observed number. The self-related coefficients were computed by making use of Fuzzy Logic . A combined approach of neural network with Fuzzy Logic is being proposed for the weather prediction system. The work has applied principle component analysis technique to the fuzzy data by making use of Autoassociative neural networks.

To predict the links in the dataset we have used the Fuzzy Link Based Classification algorithm- a subpart of Neuro Fuzzy Link Based Classification algorithm, which is a combination on the Feedforward Neural Networks (FFNet) Backpropagation techniques and fuzzy logic. FFNet was inspired from the neural system the human body. In this chapter we will first explain about the system design involved in setting up the network followed by explaining the FFNet and Backpropagation algorithm, explain the reasons for using the algorithm and then discuss about how we worked on our dataset and the steps involved in obtaining the desired output.

A cellular network is a radio network distributed over land areas called “cells”. Each cell is served by one fixed-location transceiver, which is called a “base station”. When cells are joined together, they provide wireless coverage over a large geographic area, within which mobile stations or phones can communicate with base stations and each other. Overlapping coverage areas allows transmission to be maintained even when mobile stations are moving between cells. Assigning a different set of frequencies to neighboring cells avoids wireless signal interference.

Present wireless scenario consists of homogeneous network and heterogeneous networks. In homogeneous network each base station has similar transmit power level, antenna pattern, receiver noise floor and similar backhaul connectivity. But this type of network has disadvantage of coverage hole. In heterogeneous network the macro BSs is collocated with micro, pico and femto cells. This arrangement increases overall spectral efficiency per unit area (capacity) of the network. Whereas small cell like micro, pico, femto and relays are used to avoid coverage hole and to provide mobility to the users. Not only this relays can be used to provide backhaul connectivity, where wire line link is not possible or are expensive to deploy. As determined by the information theoretic capacity limits, current cellular systems have evolved to a point where a system with one BS achieves near optimal performance. Researchers are now moving towards more advanced heterogeneous network topology which will bring the network more closely to the mobile user leading to further capacity gains [46-49]. HetNets will significantly improve the spectral efficiency per unit area by utilizing a diverse set of BSs.

Femtocells, also known as ‘home base stations’, are small low power cellular network access points that connect standard 3GPP devices to a mobile operator’s network using residential Digital Subscriber Line

Wi-Fi Internet access is fast gaining popularity as we are entering the 'unplugged ' phase of communication technology. This journey towards an unplugged world began with the first telegraph and first radio. Since then, telecommunication technology has not looked back and has shown its versatility by contributing to every field of technology. Wi-Fi has developed from synergy of wireless communication, computer networking and Internet technology. It has radically changed the way we connect and communicate.Wi-Fi (Wireless Fidelity) is a generic term that refers to the IEEE 802.11 communications standard for Wireless Local Area Networks (WLANs). Wi-Fi works on three modes namely Ad hoc, Infrastructure and Extended modes.Ad hoc network is P2P mode. Ad hoc does not use any intermediary device such as Access Point. Infrastructure and Extended modes use Access Point as interface between wireless clients.To create wireless networks with a range of about one hundred meters,802.11 technologyWith proper planning and selection antennas, same equipment can be used to make point-to-multipoint links and point-to-point links of several hundred meters.In this projectto enhance the coverage area of an access point to several hundred

FFDTD, FFBP and RBF neural network algorithms have been used to implement the ANN model for

The concentration of small cells in a network increases; measures need to be taken in order to ensure that the QoS is not degraded for the macrocell users as well as its nearest small cells. Interference managing in Heterogeneous Network in critical position .This is characteristically attained completed bright resource allocation schemes for small cells. In Heterogeneous Network, the mobile network is constructed with layers of small and large cells. This architecture is faced with the task of supply allocation (power, channel, time) for small cells in order to guarantee reliable and high quality service to both primary (macrocell) users as well as secondary (femtocell) users. In mobile network all users can be considered as nomadic, in the form of microcells, hot-spots, circulated antennas and relays becomes predictable. Therefore, for the deployment of the LTE systems the FAPs get a critical inspiring subject, mostly relating to the technical and business influences that it could signify and the method they could be combined efficiently into the LTE building.