Sparse matrix

According to, the Ansoff Product-Market Growth Matrix is an instrument in marketing that was developed by Igor Ansoff. In the Ansoff matrix, it allows the marketers to look at different ways to grow the business through existing products and markets and new products and markets. Moreover, the matrix is composed of four various strategies: - Market Penetration- market penetration is composed of existing products and markets, it occurs when an organisation enters an existing market with current

Introduction Although SmoothPay has grown successfully as a business over a short period of time, many significant challenges have arisen and must be considered in their next strategic decisions to achieve a sustainable and long term growth. Despite SmoothPay offering a unique product that allows their users to make mobile payments, the majority of consumers prefer to do cash or credit card transactions. Because SmoothPay is currently a small business, their brand has not yet been fully recognized

competitive advantage. The purpose of this report is to comment at the first part how Ryanair achieve its competitive advantage through the RBV analysis (Barney,1991), the second part will assess its approach to the diversification through the Ansoff matrix , the third part will discuss the company’s organisational culture using the cultural web modeland last part its internationalization strategy. 1. Introduction Through the Ryanair’s case study (Eleanor O’Higgins), the aim of this

The Ansoff's Matrix is a tool that helps business to decide their product and market strategies. This model describes the four strategies such as Market penetration, Product development, market development and Diversification. Markets The hotel has four vital choices

Modified OMP Chapter 4 4. Orthogonal Matching Pursuit Before discussing OMP we will go through the very basic algorithm used in CS i.e. Basic pursuit. 4.1 Basic Pursuit The intuitive approach to the compressive sensing problem of recovering a sparse vector x ∈ RN from its measurement vector Φx=y ∈ Rm, where m < N, consists in the l0 -minimization problem min┬(xϵ R^n )⁡〖‖x‖_(0 ) subject to Φx=y 〗 (4.1) This is a non

Introduction Many physical phenomena in stationary condition such as electrical and magnetic potential, heat conduction, fluid flow and elastic problems in static condition can be described by elliptic partial differential equations (EPDE). The EPDE does not involve a time variable, and so describes the steady state of problems. A linear EPDE has the general form as presented in Eq. (1), where a,b,c are coefficient functions, the term f is a source (excitation) function and u is the unknown variable

Abstract: In the reference paper, an effective and economical approach for extracting depth information and recovering sharp image is provided. Mainly, a new deconvolution method, “sparse prior” provides more accurate deconvolution results and improves depth discrimination; so, both image information and depth information can be recovered from the modified photograph taken by the camera using coded aperture. In my paper, two optimizations for the deconvolution will be provided by using regular iterative

finding K similar patches for each patch, the next step is to combine information from these patches to obtain a better estimate of the sparse representation of the HR patch. To compute a sparse representation for each patch , we need to remove its missing values, and the dictionary rows that are corresponding to the missing values. This can be done by a left matrix multiplication, similar to the previous section. Also, it is important to remove the mean intensity of each patch due to numerical stability

Abstract— Spectrum scarcity problems happen due to the spread of various wireless devices and technologies engaging static frequency access and to cope up with this demand, Cognitive Radio is a solution of enormous outlook. This article discusses spectrum scarcity problem in wide band. To solve high sampling rate problems in wide band, compressive sensing is done here.A wide band signal is passed through fading channels and then it is estimated using ℓ1 magic technique. Then receiver-operating characteristic

Anterolateral ligament (ALL), and Posterior Cruciate ligament (PCL). The knee is comprised of articular cartilage that is hyaline cartilage. Articular cartilage unlike most tissues, lack nerves, lymphatic and blood vessels. It is composed of a sparse distribution of chondrocytes