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I have worked on a paper which utilizes concepts from signal processing and machine learning, and then implements them in a low-cost embedded system. Since the work was more on the implementation side, it required less mathematics and more engineering. Furthermore, since I was using hardware from a particular company which suited my application the most, among other contenders in peripherals and price, the implementation is really hardware-dependent. Finally, I cannot seem to find similar work. In that way, it is a bit novel. Is this something which will be acceptable for say, IEEE Transactions in Industrial Electronics?

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"Stitching together" some existing algorithms is not necessarily bad, if the combination is both valuable and non-trivial. It can be argued that a lot of today's research in computer science is mostly stitching together ideas that have existed for a long time. Further, I am a huge opponent of the notion that it is somehow better / scientifically more valuable to come up with your own (almost always inferior) algorithms for well-known standard problems just so that one can claim to have a higher "novelty".

That being said, it is of course hard to answer your question without knowing the concrete work. As a rule of thumb, read through a number of back issues of your selected journal. If all of them seem to have a much broader contribution than what you have in mind, your idea may be too small (but don't let the impostor effect get you, either).

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