VLSI Architecture for QR Decomposition on MHHT Algoritm

VLSI Architecture for QR Decomposition on MHHT Algoritm A VLSI Architecture for the QR Decomposition based on the MHHT Algorithm s.n.v.sai.pratap1 k.kalyani2 s.rajaram3 Abstract: This paper presents Novel VLSI (Very Large Scale of Integration) architecture for the QR decomposition (QRD) based on the Modified Householder transformation (MHHT) algorithm. QRD of a matrix H is decomposition of matrixHinto a productof an orthogonal matrix Qand an upper triangularR. QRD is often used to solve several engineering problems in many areas. Pre-processing modules based on QRD makes the decoding in signal processing easier and implementing data detection with QRD helps to reduce the complexity of spatial multiplexing MIMO – OFDM detection. The techniques used for implementing QR decomposition are: Givens rotation, Modified GramSchmidt Orthogonalization (MGS), Householder Transformations (HHT), and indeed Modified Householder transformation (MHHT). The proposed MHHT algorithm shows best trade-off between complexity and numerical precision, and also suites for VLSI architectures. The proposed MHHT algorithm reduces computation time and hardware area of the QRD block compared to the existing Householder algorithm. Implementation of this algorithm is carried out in FPGA Virtex6 xc6vlx550tl-1Lff1759 device with the help of Xilinx ISE 14.1. Keywords: MIMO systems,VLSI architecture, QR Decomposition (QRD), Householder Transformation(HHT). 1. INTRODUCTION: The QR decomposition (QRD) is a basic matrix factorization method from matrix-computation theory used to compute two output matrices Q and R from an input matrix H, such that H = QR. QRD is often used to solve many engineering areas like least-square problems, linear system equations etc. For symbol-decoding solutions inside Spatial-Multiplexing Multiple-Input Multiple-Output (SM-MIMO) systems, QRD basically consists in simplifying demodulation tasks in suboptimal and near-optimal solutions by finding an orthogonal matrix Q and an upper-triangular matrix R from an input matrix H. Several techniques towards implementing the QRD are already reported in literature. For instance, and under the context of SM-MIMO systems, the most explored are the Modified Gram-Schmidt Orthogonalization (MGS, as a generalized improvement of the Gram-Schmidt algorithm), Givens rotation, the Modified Householder Transformations (MHHT as an enhancement of the Householder Transformation algorithm). Due to its simplicity and numerical stability, the QR factorization algorithm utilizing Householder transformations has been adopted. An overview of the main steps of the Existing Householder QR algorithm is presented. The purpose of this work is to show that when modifying existing Householder QR factorization to the matrix H, the computational complexity and hardware area gets reduced. Due to its trade-off in complexity, numerical precision, and VLSI implementation suitability, the MHHT is preferred. The contribution of this paper is to present a flexible and scalable FPGA-based VLSI architecture with competitive capabilities against other related approaches, motivated on the context of SM-MIMO demodulation solutions. The organization of this paper is as follows: Section II presents the QRD. In Section III, the exisiting HHT and MHHT algorithm is exposed. Implementation results are reported in Section IV, and conclusions are covered in Section V. 2. QR DECOMPOSITION The QRD constitutes a relevant pre-processing operation in SM-MIMO demodulation tasks [1-2]. The baseband equivalent model can be described in (1) At each symbol time, a vector S with each symbol belonging to the Quadrature Amplitude Modulation (q-QAM) constellation passes through the channel response matrix H. The received vector y at the receiving antenna for each symbol time is a noisy superimposition of the signals contaminated by Additive White Gaussian Noise (AWGN) given by n.The maximum likelihood (ML) detector is the optimum detection algorithm for the MIMO system. It requires finding the signal point from all transmit vector signal sets that minimize the Euclidean distance with respect to the received signal vector. The transmitted symbol s can be estimated by solving (2) This gives the optimal result. However, solving (2) with larger constellations and multiple antennas will result in complex calculations. Instead of solving (2) as such, the symbol estimation can be simplified by using QR decomposition of.That is where resides the usefulness of decomposing matrix H in a QR form, yielding a back-recursive dependency on elements in S without incurring into a BER (Bit Error Rate) loss [3-4]. With this practice, the computational complexity is reduced. The detected vector is computed based on the ML algorithm with QR decomposition as given in (3) (3) where is in upper triangular form, approximation of is computationally simpler with the aid of (3). Note that for MIMO-OFDM systems operated in stationary environments, the channel matrix remains almost the same. Thus, QR decomposition of the channel matrix can be done only once to get matrix. On the other hand, the calculation of must be updated for every incoming signal. 2.1 QRD IMPLEMENTATION The techniques used for QR decomposition are: Gram–Schmidt algorithm obtains the orthogonal basis spanning the column space of the matrix by the orthogonality principle. Using a series of projection, subtraction, norm and division, the column vector of the unitary matrix containing the orthogonal basis can be acquired one by one and upper triangular matrix is also obtained as a by-product. Householder Transformation (HHT) tries to zero out the most elements of each column vector at a stroke by reflection operations. The upper triangular matrix is derived after each transformation matrix being applied to every column vector sequentially. The unitary matrix involves the multiplications of these Householder transformation matrices and thus the complexity is much higher. On the other hand, Givens Rotation (GR) zeros one element of the matrix at a time by two-dimensional rotation. If an identity matrix is fed as an input, the unitary matrix will be calculated by using the same rotation sequence when the upper triangular matrix is obtained (Malstev 2006; Hwang 2008 and Patel 2009).The Gram–Schmidt algorithm has the disadvantage that small imprecisions in the calculation of inner products accumulate quickly and lead to effective loss of orthogonality.HHT method has greater numerical stabilitythan the Gram–Schmidt method. Givens method stores two numbers c and s, for each rotation and thus requires more storage and work than Householder method .Givens rotation requires more complicated implementation in order to overcome this disadvantages. Givens rotation can be beneficial for computing QR factorization only when many entries of matrix are already zero, since nullifying certain matrix elements can be skipped. Unlike Givens Transform, Householder Transform can act on all columns of a matrix, and require less computations for Tridiagonalization and QR decomposition, but cannot be deeply or efficiently parallelized. Householder is used for dense matrices on sequential machines, while Givens is u sed for sparse matrices or/on parallel machines. 3. QRD using Householder Transformation In this section, the existing Householder Transformation algorithm is described, followed by proposed HHT method architecture is demonstrated in detail. 3.1 Householder Transformation Householder QR algorithm gradually transforms H into an upper triangular form R by applying a sequence of Householder matrices (multiplies H from the left with Q). Householder transformation is performed by projecting a multi-dimensional input vector onto a plane zeroes multiple elements at the same time. An nÃâ€"n matrix H of the form , (4) is called a Householder matrix. The vector is called a Householder vector. Pre-multiplication of the coefficient matrix with is used to zero out appropriate elements of. It is easy to verify that Householder matrices are symmetric and orthogonal. The Householder matrix block involves the computation of an outer product which requires complexity operation. However, the practical time requirement of using to zero out elements in is lower than that of computing a full outer product. This is because of the tedious computation of the full matrix which is not necessary in practice. Householder reflections work well for introducing large number of zeros using just one matrix multiplication (computing). Normally, all the elements below the diagonal of an entire column of the matrix are eliminated by one Householder reflection. However, this leads to a difficulty when Householder transforms are implemented on parallelly. One reflection affects multiple rows, and therefore, it is difficult to achieve fine-grained parallelism in the operation. The algorithm for Householder transform is given in Table 1. and its block diagram is given in Figure 2. Fig. 2 Block diagram of HHT Table 1 HHT algorithm End Householder vector block: The conventional method of Householder algorithm for decomposing channel matrix is given in Table 1. Initially, the channel matrix is assigned to matrix. It can be periodically updated by following steps to obtain upper triangular matrix. The first column of is assigned to ‘a’ vector. After that the norm value of ‘a’ is calculated and assigned it to ‘g’. The Householder vector ‘v’ is the division ‘u’ and‘t’ which is the norm operation of vector selection . Householder matrix block: The output of Householder vector is given as input to Householder matrix block. Finally, H is computed by The above operation can be updated upto n times to obtain the upper triangular matrix and unitary matrix. It is given below, (5) Q = (HnHn-1†¦H1) T (6) Here the matrix is given to the input of channel matrix to update its vector value. The orthogonal matrix is computed by the multiplication of ‘n’ Householder matrix. Hence its complexity increases and also it occupy more hardware area. If the matrix size increases, the hardware area also increases tremendously. So there is need to reduce the hardware complexity of this block. 3.2 Proposed HHT method The existing method of Householder reflection requires large hardware area and computation time. Householder transformations also provide the capability of nullifying multiple elements simultaneously by reflecting a multi-dimensional input vector onto a plane. However, VLSI implementation of the Householder algorithm needs square-root, multiplication and division operations, which require high hardware complexity. To resolve this issue, a novel Householder algorithm is presented that use series of simple Householder projections, which can be easily implemented using simple arithmetic operations. The proposed algorithm as given in table2 has lesser number of computations compared to the existing algorithm. In Figure 3, the block diagram of modified method is given. It shows two major sub blocks (i.e.) householder vector block and householder matrix block. Householder vector block is same to the previous method of computing ‘v’ with extra weight vector computation. Here modification taken in the Householder matrix block to eliminate matrix multiplication. The vector ‘v’ subtracted from ‘f’ and column vector of channel matrix to give ‘H’ value. Fig. 3 Block diagram of MHHT. In the first step, matrix H is reduced to with all zeros below the diagonal element in the first column by computing the sign of the pivot element d and weight value w. Compared to the previous algorithm, number of steps required to obtain the first matrix can be reduced. For example, if the initial channel matrix of 4Ãâ€"4 undergone to Householder reflection, then it reduces the matrix with all zeros below the first element. The computation of Householder vector in the existing algorithm requires large memory and area. Because is a 4Ãâ€"4 matrix, multiplication of become complex process. To avoid such a task, column vector of matrix has been taken one by one and process it iteratively to obtain the upper triangular matrix. After computation of the first step the matrix size reduced to. After that, the sub matrix of size 3Ãâ€"3 is taken and the steps can be applied repeatedly. The algorithm to compute Householder Vector block is given below. Table 2 HHT algorithm End Repeat above steps for right bottom (n-1)*(n-1) matrix of R Householder vector block: In this Householder reflection algorithm, it transforms the column (7) into the vector of the form (8) where the diagonal element (9) The Householder vector can be computed by, (10) where and This block computation is same as that of previous Householder vector block with a little modification in the weight value. Householder matrix block: After obtaining the Householder vector, the output vector is given to the input of Householder matrix block. The computation of this block is very simple compared to previous method of Householder matrix block computing. The Householder matrix element algorithm is given below, (11) where It reduces the channel matrix to its upper triangular form in steps. To reduce the complexity of computing Q, here the output vector y’ has been taken directly and its algorithm is given below, (12) So the execution time for computing the upper triangular matrix and output vector is very less when compared to conventional Householder reflection algorithm. This reduces the hardware area for the Householder matrix block. The QR decomposition using modified Householder transformation algorithm is simulated by taking ‘a’ as input channel matrix, ‘zb’ as output vector and ‘upper’ as upper triangular matrix. The unitary or orthogonal matrix ‘Q’ need not to be calculated. The output vector in (3) can be computed from the updated Householder vector ‘v’. Also the extra time needed to calculate ‘Q’ can be reduced. So the speed of decomposing the channel matrix can be increased tremendously. 4. Results and Discussion QR decomposition algorithm is required as a pre-processing unit for many MIMO detectors. The accuracy of the channel matrix QR decomposition does not have an impact on the MIMO detection process and finally receiver’s bit-error-rate (BER) performance. The existing and proposed Householder algorithms are downloaded on to Xilinx device xc6vlx550tl-1Lff1759. The synthesis results are compared to show the area efficiency of the proposed one. The channel matrix H elements are represented in floating point representation of 16 bits comprising 1 for sign bit,3 bits for decimal part and 12 bits for fractional part. The 16 bit representation shows an numerical precision oscillates around the interval[10-6,10-5] for both existing and modified algorithms . The computation of column vectors of the R matrix can be parallelised in modified algorithm and thus improvement is obtained in computational time of 49.7% reduction.The computational time for proposed algorithm is about 194.84ns,whereas exisiting algorithm is about 394.56ns. Modified algorithm reduces the matrix computation into vector multilications for some extent and thus reduces the hardware area as obtained from the synthesis report. Table 3 Synthesis report for Conventional Householder algorithm Logic Utilization Used Available Slice LUTs 11142 343680 Bonded IOBs 768 840 BUFG/BUFGCTRL’S 0 32 DSP48E1s 261 864 Table 4 Synthesis report for Proposed Householder algorithm Logic Utilization Used Available Slice LUTs 7634 343680 Bonded IOBs 385 840 BUFG/BUFGCTRL’S 1 32 DSP48E1s 70 864 Table 5 Comparison result Logic Utilization Conventional HHT Proposed HHT % reduced Slice LUTs 11142 7634 31% LUT Flip flops 768 385 49.8% Bonded IOBs 0 1 DSP48E1s 261 70 73% 5. Conclusion To reduce the computational and hardware complexity, Householder transformation algorithm for QRD has been modified. The computation of Q is the tedious process in the existing algorithm. In this work, it can be overcome by directly computing output vector. It reduces the computation time by 52.38% and also reduce in hardware area compared to previous HHT algorithm (Slices – 31%, LUTs – 49.8%) presented in the QRD. Thus it is evident from the comparison result that the number of slices and 4 input LUTs required in FPGA implementation of QR Decomposition is reduced thereby making the low complex design which can meet the specifications of most OFDM communication systems, including VDSL, 802.16, DAB and DVB. In future, this work can be extended to implement K-best LSD and Turbo decoding of LTE receiver. References Lee, K.F. and Williams, D.B.: A space-frequency transmitter diversity technique for OFDM systems. In Proc. Global Telecommunications Conf., San Francisco, CA, pp. 1473-1477. (Nov. 2000) H. Kim, J. Kim, S. Yang, M. Hong, and Y. Shin, â€Å"An effective MIMO–OFDM system for IEEE 802.22 WRAN channels,† IEEE Trans. Circuits Syst. II, Exp. Briefs, vol. 55, no. 8, pp. 821–825, Aug. 2008. H.-L. Lin, R. C. Chang, and H.-L. Chen, â€Å"A high speed SDM-MIMO decoder using efficient candidate searching for wireless communication,† IEEE Trans. Circuits Syst. II, Exp. Briefs, vol. 55, no. 3, pp. 289–293, Mar. 2008. L. Boher, R. Rabineau, and M. Helard, â€Å"FPGA implementation of an iterative receiver for MIMO–OFDM systems,† IEEE J. Sel. Areas Commun., vol. 26, no. 6, pp. 857–866, Aug. 2008. M.-S. Baek, Y.-H. You, and H.-K. Song, â€Å"Combined QRD-M and DFE detection technique for simple and efficient signal detection in MIMO–OFDM systems,† IEEE Trans. Wireless Commun., vol. 8, no. 4, pp. 1632–1638, Apr. 2009. C. F. T. Tang, K. J. R. Liu, and S. A. Tretter, â€Å"On systolic arrays for recursive complex Householder transformations with applications to array processing,† in Proc. Int. Conf. Acoustics, Speech, and Signal Process., 1991, pp. 1033–1036. K.-L. Chung and W.-M. Yan, â€Å"The complex Householder transform,† IEEE Trans. Signal Process., vol. 45, no. 9, pp. 2374–2376, Sep. 1997. S. Y. Kung, VLSI Array Processors. Upper Saddle River, NJ, USA: Prentice-Hall, 1987.

Essay --

â€Å"You feel mighty free and easy and comfortable on a raft.† (Twain, 181). In Adventures of Huckleberry Finn written by Mark Twain. Huck is a young boy in the 1840s; he runs away from home and floats down the Mississippi River. He meets a runaway slave named Jim and the two go on a series of adventures leading to Jim’s freedom. Throughout the novel, Huck slowly changes his views of racism. As Huck begins to have a change of heart, he gradually begins to decide between right and wrong. As a result, Huck faces moral dilemma of being between the world's prejudice that he learned growing up, and the lessons Jim has taught him throughout the story about the evils of racism. Huck’s struggles are revealed through the conflicts with his moral beliefs and cultural dilemmas. This is shown through his conflicts with himself, with other characters and society. Huck struggles with himself through his moral beliefs. Huck struggles with himself because he grows up in the lower class and when he moves in with the Widow it is hard for him to adjust to the life of the upper class. Huck is speaking to the reader at the beginning of the novel about events that have occurred in the previous novel, The Adventures of Tom Sawyer. Huck explains how he was adopted by The Widow Douglas and how she tried to civilize him. â€Å"The Widow Douglas she took me for her son, and allowed she would sivilize me; but it was rough living in the house all the time †¦ when I couldn’t stand it no longer I lit out †¦ But Tom Sawyer he hunted me up and said he was going to start a band of robbers, and I might join if I would go back to the widow and be respectable. So I went back† (2). This passage shows how Huck is being civilized by the widow and since he is from the lower class ... ...uck’s struggles are revealed through his conflicts with his morals and beliefs. This is shown through the conflicts with himself, other characters and society. Huck struggles with himself when he is trying to send a letter to the Widow Douglas about Jim where being. Huck contemplates but can only think of reason to tear the letter up. Also, Huck struggles with others because many characters influence Huck’s morals and beliefs. Jim has a big effect on Huck’s life because he changes Huck’s belief of Africans. Lastly, Huck struggles with the expectations that society has put on him. As Huck begins to have a change of heart, he gradually begins to decide between his morals and beliefs. Therefore, Huck faces moral dilemmas of being between the world's prejudice that he learned growing up, and the lessons Jim has taught him throughout the story about the evils of racism.

Adam Smiths Invisible Hand

Page 41 questions 2-5, 7 and 9 2) Honoring tradition, because Traditional Economies are based on customs and beliefs of its people, aka cultural things, which is often a tradition. 3) Economic decisions in a command economy are made from government officials considering the resources and needs of the country and distribute resources based on their judgment. 4) Consumers can spend their money as they want; producers decide what goods or services they’ll offer. 5) Adam Smith’s â€Å"invisible hand† does function in both traditional economies and command economies, too.In traditional economies they base everything on survival. To survive, you must think about yourself but more so about your peers to make sure you all produce and consume what you need. In command economies, the government distributes based on their judgments but still after considering what the people need. 7) Well defined economic roles and goals can be a strength in a traditional economy because th ere isn’t much disagreement going on about it. It can also be a weakness because people may not be able to get the role they desire due to their beliefs. ) I believe this is a traditional economy because in a traditional economy, tradition sort of assigns their jobs to them and by belief they can’t change this. Producers have to use materials as custom says, so they may not be able to use them as they would like to. And since they go by tradition, people can’t really change or have any say in the basic economy questions, or how they’re answered. Page 47 questions 2-5, 9 2) So they can provide for everyone. 3) Leaders can use the nation’s resources to produce items that may not make money in a market economy and even the sick or old who aren’t productive economically are provided for. ) Prices are below what they could be worth, and leaders are more unaware of local conditions, making their decisions wrong. The leaders are paged no matter the ir output. No private property makes people want to use resources wrong more. 5) The state rules the individuals every move. 9) Page 57 Questions 2-5, 7, 9 2) Private property, specialization, consumer sovereignty, competition, government involvement, voluntary exchange, profit. 3) People free to make their own economic choices, people are free to develop interests and talents they like. Profit. ) No mechanism for providing public goods and services, cannot provide security to those who cant be productive. 5) Efficiency serves as a reward for hard work and innovation, and if they were inefficient with distributing resources, they would make less profit. 7) What payments they pay to the factor market are sent as income from resources to the households who pay consumer spending to the product market which sends business revenue right back to businesses. 9) The government in this economy can try to help provide for those who can’t be productive and try to do some public services and offer goods.Page 63 questions 2-5, 8-9 2) A market driven mixed economy is an economy where the people want a mixture of command economies and market. France is one of these, their economy emphasized the command system in years following WW2, in the 80’s they witnessed the dissatisfaction with performance of the gov’t. So the French lowered the command role. 3) 4) 5) 8) 9) #1: The producer should be able to decide how many of the digital cameras or of everything else to produce. Because he is producing that good, he should be able to decide who to make it for, as well. #2:

Animal Experimentation Is Vital - Free Essay Example

Sample details Pages: 5 Words: 1512 Downloads: 2 Date added: 2019/04/12 Category Biology Essay Level High school Tags: Animal Testing Essay Did you like this example? Whats the Price Animal rights is based on the belief that non-human animals have rights similar and equal to humans. However testing is clearly split down the middle. Today animals are used in the development of all kinds of things, such as medical research by the use of animal experimentation. Animal testing provides some people with hope for potential cures for viruses but testing on live animals is not necessary. Today, advanced technology takes care of that for us. By using models, we can replicate things that animals cant. You may ask yourself so whats the big problem? Well the problem is these animals are cruelly mistreated and most likely will lead to death. These animals are born with defects and experimented on. Animal testing should be banned because its cruel, unnecessary and not effective. Animal testing is not only down right wrong, its also unjust in todays society. Don’t waste time! Our writers will create an original "Animal Experimentation Is Vital" essay for you Create order Animal experimentation is vital to the development and the future of the human race. Scientists believe that animal research saves thousands of lives worldwide and is reasonably safe. Scientists rely on animal models to learn how diseases process and work on developing potential treatments. Animal experimentation is saving the lives of people who had little hope for survival and without recent developments these cures would not be possible. In order for scientists to look for cures, they have to use animals as test patients to see how a disease continually progresses in a living body (Trull 2). Scientists cant just have any species. They have to have species that is close to a humans genome, such as mice or even primates. Mice are particularly known as the most common model for disease research. Infact, mice share over 92% genetic similarity to us humans (Trull 2). Over the past century, animal research has proved to be vital to stamp out several major epidemics of infectious disease. Most notable is the cure of smallpox. By testing on cows, scientists were able to develop a vaccination for the disease. Also, decades of long research with monkeys, dogs, and mice gave us a cure to get rid of polio. These non-human primates have also contributed to the research and the development of drugs that fight cancer, malaria, HIV/Aids and many more diseases (Animal Testing 1). Research and experimentation has allowed us to increase the U.S. survival rate of cancer by more than 60% between 2001-2007. (Trull 1). All because of animal experimentation, those numbers were possible. Also, more recently, animal research has helped stop potential international threats, such as Avian Flu and Severe Acute Respiratory Syndrome or also known as SARS (Animal Testing 2). Animal Research has helped researchers better understand these diseases and how they spread. As a result, we can contain and avert these global pandemics. Recently, the polio virus is another example of how valuable animals are to us. An anti- Ebola serum has showed remarkable success when tested in Rhesus monkeys. Since then, the serum has been credited with saving the lives of two Americans infected with the virus (?Trull 2). The serum is so successful that the FDA has offered 42 million to the company, who developed the treatment known as, ZMapp. Furthermore just last September, a Japanese women became the first person to undergo experimental stem-cell treatment for blindness (Trull 3). Animal research has allowed us to get that much closer in restoring vision. While this research is helpful to humans, its also helpful to other animals. Wild primates are also susceptible to Ebola especially gorillas. They are so susceptible, they have a mortality rate of 95% when affected with the disease (Trull 2). One-third of the worlds primates have been killed off in the past few decades in Central Africa. A cure would save the lives of animals and humans. The greatest medical contribution may still lie in the future but its going to be tackled because of animal experimentation and research. Animals have a lot more in common with us humans than you may think. Recent breakthroughs in technology, show we have a better understanding of how animals feel pain and suffering just like we do. Some animals like primates are not only biologically similar with humans, but they are also similar in neurologically. What most people dont see is that these animals have mental lives comparable to ours. The animals can not only feel sensitivities, but they can also feel pain and deprivation (Jeory 2). We as humans definitely differ in our physical appearance, but we have a lot more in common with them then appearance. Animals in labs are cruelly mistreated and are intentionally injured for various of reasons. Lab animals on a daily basis are intentionally infected with diseases, force fed chemicals, blinded burned, mutilated, and left to suffer without veterinary care for treatment (Moore 1). How cruel is that! Imagine you and your family being put in small cages and treated inhumanly. No one could imagine that happening to them and their families so why do we think its ok to do these actions against living animals. We may have to test on the experimenters to get them to see the point that its not ok. Test against humans would not only affect us physically, but mentally as well and thats what we are doing to animals. According to Dr. Jane Goodall, a famous primatologist and peace keeper, animal testing is inhumane and morally wrong (Moore 2). She said, I and my team have studied chimpanzees, our closest living relative for over 50 years. I can state categorically that they have a similar capacity for suffering, both mental and physical, and show similar emotions to ours. She also said, theres no doubt other animals that they have studied can not feel fear, depression, anxiety frustration and so on. To put them into cases in labs are also morally wrong in her opinion. Coming from a women that has physically interacted and studied animals for over 50 years has to know whats shes talking about. Her entire life is dedicated to these animals who have no voice. Experimentation is not only morally wrong but its painful to all animals affected. We need to come together as a world and end testing for once and for all. Change is upon us and we can go away from these actions by recent technology, but for some reason were not. Animal experimentation is wrong especially when you know that we dont have to do it in todays society. Today, we can now replicate human organs on microchips to test the potential impacts of drugs, diseases, and more. Not only can we replicate organs, but we can also simulate diseases progressing in the human body by using computer modeling (Moore 3). Modeling accurately predicts the ways in which the new drugs will react in the human body. Also brain-imaging techniques allow the human brain to be studied safely in very effective methods. We now have the capabilities to study the human brain all the way down to a single neuron. Thats incredible! (Jeory 3). Technology can replace the use of animals in exploratory research and many standard drug tests. During experiments, animals are intentionally brain damaged and with this technology, we can replace their crude behavior. We should continue to develop even more advanced alternatives so maybe scientists can see that technology is better than actual testing and it has more capabilities than animals would give us. Finally, animal experimentation is bad science and time and time again experiments show high failure rates. Not only does animal experiments waste the lives of animals, but it also wastes human lives. Numerous of methodical reviews have even documented the enormous failure rates of experiments on animals to benefit humans in the areas of neurodegenerative disease, neuropsychiatric disorders, cardiovascular disease, stroke, cancer and many more areas (Gluck 4). Nine out of ten experimental drugs that pass animal studies, fail in humans and thats why you see loss of human life. The few drugs that are even re-labeled or pulled from the store shelves have already put their effects on humans that purchased them. Many people get sick or die before there is ever a chance to fix it. Decades of HIV and Aids experiments have failed to produce effective vaccines for humans even though at least 85 were successful in primate studies. Even John Loannidis, Professor of Medicine and Health Research at Stanford University says, its impossible to rely on animal data to predict the benefit and risk ratio in human subjects. Animal experimentation is an easy change but theres one issue with the change and thats money. At the end of the day, corporations and universities are not making changes because current advanced technology cost more money than testing on animals. As you can see, animal testing is very twisted and cruel. Depending on what side you are on, you may not see it that way. People believe animal testing is a necessity in todays society but its not. Through my research, I discovered there are many different solutions but to end testing, both sides are going to have to come together to make compromises to make difference in the world.